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Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal relationship and fuzzy partially causal relationship
Abstract
We discuss fuzzy implications of fuzzy cognitive map (FCM), which has been used in various fields for representing causal knowledge. To accomplish this objective, fuzzy implications of FCM are thoroughly investigated with extensive examples. FCM is a fuzzy signed digraph with feedback, which can model the real world as a collection of concept variables and causal relationships. Therefore, FCM has been used as a new knowledge acquisition scheme in expert systems domain, especially in abstract and fuzzy domains where the relationships between concept variables are causal. However, fuzzy implications of FCM have been misunderstood, leading to the misuse of FCM. In this sense, we reveal new fuzzy implications of FCM and use them for forming causal knowledge. Those fuzzy implications proposed herein include fuzzy causal relationship and fuzzy partially causal relationship. Extensive definitions and theorems are proposed to show the validity of our proposed fuzzy implications.
... This section recalls the notions of fuzzy causal relationship and fuzzy partially causal relationship as given by Kim H.S. and K. C. Lee [50]. ...
... Buying by institute investors in the stock market example [50]. ...
... From now on, we assume that "buying"-"selling" and "increase"-"decrease" are the corresponding pairs of quantity fuzzy sets (Q i ) and dis-quantity fuzzy sets( ~ Q i ). In other words, we assume that (FCR-2) is equivalent to (FCR-3) in stock market given in example [50]. ...
... During the interview, the study's objectives and the research procedure were presented, allowing for a better understanding of the study by the ICT manager. As a result, the list of the main concepts and the description of the leading information about security strategies adopted to treat and prevent problems caused by cyberattacks in telehealth services were obtained, considering the ICT manager's perception [27]. ...
... A FCM can be described as a fuzzy graph containing the concepts to be casually assigned in the nodes and the relationships in the edge arrows [25]. The procedure for creating the FCM can be defined in three main steps [27]: ...
Hospital organizations have adopted telehealth systems to expand their services to a portion of the Brazilian population with limited access, mainly due to the geographical distance between their communities and hospitals. The importance and usage of those services have increased recently due to the COVID-19 state-level mobility interventions. These services work with sensitive and confidential data, containing medical records, medication prescriptions, and results of diagnostic processes. Understanding how cybersecurity impacts the development of telehealth strategies is crucial for creating secure systems on daily-based operations. In the application reported in this article, the Fuzzy Cognitive Maps (FCMs) translated the complexity of cybersecurity in telehealth services into intelligible and objective results in an expert-based cognitive map. The tool also allowed the construction of scenarios simulating the possible implications caused by common factors that affect telehealth systems. FCMs provide a better understanding of cybersecurity strategies using expert knowledge and scenario analysis, enabling the maturation of cybersecurity in telehealth services.
... Disadvantages of causal maps include: 1) the encoding into the maps/diagrams participants knowledge, ignorance, misconceptions and biases (Kosko, 1992b); (2) the possibility of modelling "what-if's" although "why's" remain indeterminable (Kim & Lee, 1998); (3) no real-value parameter estimates of inferential statistical tests are provided (Craiger et al., 1996); (4) no regard to temporal component (time) and thus unable to model transient behaviour within an system (Schneider et al., 1998;Hobbs et al., 2002); (5) an inability to deal with co-occurrence of multiple causes shown by "and" conditions; and (6) "if & then" statements can only be coded qualitatively (Schneider et al., 1998). ...
... The maps as such do not provide any information on the causation (the 'why' aspect) associated with the drivers (see Kim & Lee, 1998). In this map, this has partly been circumvented through the indication of the dampening or amplifying effect the stressors have on other, related stressors (i.e. the causation). ...
Small-scale fishers and the communities they support face a range of challenges brought on by change in their marine social-ecological systems (SES). The resulting complexity and uncertainty hamper their ability to achieve sustainability while holding implications for decision-making at various scales: fishers need to respond proactively to change at smaller scales of operation while managers need to apply the principles of ecosystem-based management approaches such as an ecosystem approach to fisheries management (EAF) at larger scales.
Using the small-scale fishing communities of South Africa’s southern Cape as a case study, this thesis explores how structured decision-making tools (specifically causal mapping, Bayesian belief networks and scenario planning) can be applied in an interactive and iterative scenario-based approach with disenfranchised fishers in support of decision-making at multiple scales. Specifically, this thesis aims to (1) determine and describe major stressors in the fishery system of the southern Cape using the perspectives from the crew component of its linefishery; (2) establish what interactions and feedback loops (drivers of change) exist and interact at various scales; (3) use Bayesian belief network modelling in an iterative participatory process to establish the prominent drivers of change within the fishery system (from the crew perspective); (4) develop, together with fishers, four stories of what the future may hold for one of the towns using an iterative participatory scenario planning exercise, based on some of the principles of transformative scenario planning approaches; (5) evaluate the contextual suitability of the application of the various tools used throughout the research process and recommend next steps in a larger scenario planning process; and (6) create an opportunity for fishers to engage in a process that could enhance their understanding of possible change response strategies through learning, thereby increasing adaptive capacity in the support of the implementation of an EAF in South Africa.
As a start, drivers of change were established and documented, complementing earlier research. This was done to ensure that all user groups’ views were represented in an initial causal map showing the drivers of change in the fishery system. In the causal mapping process, stakeholders from towns across the research area mapped out drivers of change in an iterative process. The causal maps not only helped to frame the system but also revealed important hidden drivers of change as well as feedback loops. The Bayesian belief network and scenario story development took place in the town of Melkhoutfontein. Bayesian belief networks provided insights into system uncertainty while serving as a problem reframing tool. The outputs of both the causal maps and Bayesian networks were then used to construct four scenario stories depicting possible futures in 30 years, based on inputs obtained from research participants in a visioning workshop. These scenarios not only provided examples of plausible futures under certain conditions but also promoted new ways of thinking about the drivers of change and their likely effects, highlighting the interconnectedness in the system.
Implementing the overarching approach has provided marginalised fishers with an opportunity to freely air their views while engaging with new tools. The process does not only benefit fishers and their communities (at the small scale) but also provide valuables insights into how fishers view and experience the marine SES of the southern Cape. Moreover, the approach has identified ways in which challenges presented by scale in SES can be better addressed to ensure more effective decision-making in the pursuit of sustainability. This understanding and insight are integral for moving closer to the implementation of the EAF in South Africa, where the integration of the social dimensions of marine social-ecological systems into coherent evaluation and planning continues to be problematic.
... According to Kim and Lee (1998), building FCMs takes place in three fundamental stages. First, the reason for creating the FCM needs to be clarified since, if the goal of the mapping exercise is unclear, the search for the most important factors may lack direction and the map might reach a size that makes analysis difficult. ...
... Solana-Gutiérrez et al. (2017: 261) observe that, overall, "the construction of a[n] FCM requires the input of human experience and knowledge of the system under consideration". Kim and Lee (1998), Papageorgiou et al. (2002), Mazlack (2009), Salmeron (2009), Yaman and Polat (2009), Carlucci et al. (2013, Ferreira and Jalali (2015), Nápoles et al. (2016), and Misthos et al. (2017), among many others, emphasize that the concepts included in FCMs can have three types of cause-and-effect relationships. These allow the degree of influence w that one concept has over another to be understood and analyzed. ...
In an increasingly digital world, almost anything can now be done through a computer or smartphone. Digital entrepreneurship is capitalizing on this trend, which brings numerous advantages to firms and society at large. However, the determinants of digital entrepreneurship’s success are still unclear, as well as how they relate to each other. This study sought to develop a fuzzy cognitive map (FCM) to identify and analyze the determinants of digital entrepreneurship. Two group sessions were held with a panel of decision makers who deal with the digital entrepreneurship phenomenon every day. Based on their shared experience and knowledge, an FCM was developed and validated for this research context. Static and dynamic analyses facilitated a deeper understanding of the cause-and-effect relationships between the determinants of digital entrepreneurship, resulting in a well-informed framework that was validated by the panel members. This methodological procedure enabled an objective analysis of the dynamics behind digital entrepreneurship. The advantages and limitations of our constructivist framework are also discussed.
... In other words, there are three possibilities for each cause-and-effect relationship between the concepts/criteria: (1) positive causality (w ij > 0) (i.e. an increase/ decrease in the value of C i increases/decreases the value of Cj); (2) negative causality (w ij < 0) (i.e. an increase/decrease in the value of C i increases/decreases the value of C j ); and (3) no causality (w ij = 0), which indicates an absence of relationship between C i and C j (cf. Kosko 1986;Kim, Lee 1998;Kok 2009;Salmeron 2009;Kang et al. 2012;Papageorgiou et al. 2012;Carlucci et al. 2013;Ferreira, Jalali 2015;Ferreira 2016). ...
... Carlucci et al. (2013) state that it is possible to initiate an FCM creation process through any of the following techniques: (1) from questionnaires; (2) by extraction from written texts; (3) by drawing it from data that shows cause-and-effect relationships; and, lastly, (4) through interviews with people who draw a map directly, such as one or more experts or a work team, for instance. In this study, and following Kim and Lee's (1998) orientations, the development of the FCM was initiated through group meetings, i.e. face-to-face sessions with experts, named decision makers, who had specific knowledge about the subject in question (see also Ferreira et al. 2016a). Other factors were also taken into account in choosing the decision makers, such as their availability for participating in two group meetings with an approximate duration of 4 hours each. ...
The recent economic climate has had direct repercussions on people's daily lives. This has occurred not only in how they use payment instruments, but is also evinced in new concerns adjacent to technological advances, people's safety and the credibility of financial institutions. In this regard, the banking sector has had a crucial role in countries' economic development, making it increasingly important to understand how the banking system operates and what payment instruments are available to users. Relying on specialized literature and the application of fuzzy cogni-tive mapping, this study aims to understand the cause-and-effect relationships between customers' preference factors in using payment instruments. The results show that usability aspects and safety concerns constitute the factors which users pay more attention to. Strengths and limitations of our proposal are also discussed.
... In the scientific theories and models this means that we have to operate in such networks of variables in which various interconnections prevail between them. Robert Axelrod and Bart Kosko have provided a partial resolution within time series analysis to this problem with their ideas on the cognitive maps, and quite many fuzzy applications are already available in this area [2,7,8,15,16,18,27]. The well-known examples of other applications are the Bayesian networks, theory of networks, structural equation modelling, answer tree analysis, and even factor analysis [5,39]. ...
... They may also include feedback operations, and hence in these systems everything may depend upon everything else. We usually apply these maps to such simulations in which we aim to forecast the complex phenomena on the time axis [7,8,15,18,27]. In statistics the structural equation models are used for this purpose (e.g., Mplus™, LISREL™, AMOS™) as well as time series analysis, but the fuzzy cognitive maps are usually simpler and more robust in model construction. ...
Concept maps and Lotfi Zadeh’s fuzzy extended logic are applied to such computerized approximate reasoning models as modus ponens and modus tollens. A statistical application is also sketched. A pedagogical approach is mainly adopted, but these ideas are also applicable to the conduct of inquiry in general.
... FCMs have been demonstrated as an effective modeling method in precision agriculture, with learning methodologies based on algorithms developed for induced fuzzy cognitive maps to adapt cause-and-effect relationships in FCM models [2]. This approach enhances the effectiveness and strength of FCMs by updating the initial knowledge of human experts and integrating their structural knowledge [3]. ...
... A list of all features was compiled and redundant features (e.g., plural forms of a word, different names for the same concepts) were merged. Following past research (Kim and Lee 1998), when two features represented opposite directions of the same concept, the more prevalent feature was retained and the other was renamed, with the direction of influence reversed. The interaction strengths between features were then scored, with high interactions scored as (+/-) 0.75, medium as (+/-) 0.5, and low as (+/-) 0.25 (Harary et al. 1965). ...
The Interior of Alaska is one of the few remaining places in the world with intact ecosystems. Protected areas in this region, particularly Denali National Park and Preserve and Denali State Park, are high-profile tourism destinations situated in a rural landscape that is inhabited by a diverse array of stakeholders. Public land management agencies are faced with the challenging task of engaging these rural residents in discussions about their relationships with a rapidly changing landscape to understand change and growth. This study evaluated residents' perceptions of social and ecological dynamics of protected areas in Interior Alaska using data from fuzzy cognitive mapping exercises that were part of focus groups and interviews across six local communities. Guided by an exploratory resilience framework, we established a baseline understanding of features that characterized social and ecological conditions at a regional scale. Results showed how residents valued a variety of socio-cultural, socioeconomic, and ecological features of the landscape. The region was predominantly characterized by tourism, sense of community, subsistence, and wilderness. Climate change and large-scale development were the primary drivers of change. Our findings also showed that although the characterization of the region was shared in many ways, there were nuanced differences articulated by residents in each community that warrant attention. These findings provide a structured platform for building resilience and interpreting variability in visions for the future.
... The effect of one concept to the others can be negative or positive, with a fuzzy degree of causation [9]. The determination of the sign and the description of the causal relationships, using a linguistic notion follows, and then linguistic weights, such as "strong", "weak" etc., corresponding to fuzzy sets, are assigned to each arc. ...
Motivated by the brainstorming process of human beings, a novel learning Fuzzy Cognitive Map (FCM) model named Brainstorming Fuzzy Cognitive Map (BFCM) is proposed. The proposed model is based on a state-of-the-art optimization algorithm, named Determinative Brain Storm Optimization, which is utilized to automatically adapt the weights of the FCM structure. In this study, BFCM is applied for safe outdoor navigation of visually impaired individuals. This application ensures the avoidance of static obstacles in an unknown environment, by taking into consideration the output of an obstacle detection system based on a depth camera. The simulation results show that the proposed model can effectively assist the users to avoid static obstacles and safely reach a desired destination, and they promise a wider applicability of the model to other domains, such as robotics.
... In several cases, the same variable was described by a different name or term in the various individual maps; these variables were identified, allocated a common name and redundant (duplicate) variables were removed. Two variables representing the same concept, but with opposing directions, can be included in an FCM with the same direction by altering the polarity of the interaction (Kim and Lee, 1998;Vasslides and Jensen, 2016). Based on this, variables in the current study with opposing directions, but representing the same concept, were combined and given the direction indicated by most participants. ...
Fuzzy Cognitive Mapping (FCM) is a participatory modelling tool used to explore complex systems by facilitating interdisciplinary cooperation and integrating a variety of knowledge systems. Here FCM was used to explore marine microfiber pollution. Through individual interviews with representatives from the research, industry, water and environmental sectors, five stakeholder FCMs were developed and used to produce an aggregated community FCM in a stakeholder workshop. Stakeholder FCMs and the revised community FCM were used to compute how the modelled system reacted to changes under two scenarios developed during the stakeholder workshop; (i) Green Shift and (ii) increased textile consumption and production. Significant differences were observed in scenario results from the stakeholder-based models and the community-based model. For societal challenges characterized by unknowns around the problem and potential solutions, inclusion of a variety of knowledge systems through FCM and deliberation processes contribute to a more holistic picture of the system and its uncertainties.
... Participants can numerically/qualitatively determine the strength of causal relationships (e.g., the numeric edge weights between the nodes or qualitative Likert scales to specify the magnitude of relationships ranging from very weak to very strong). Based on fuzzy sets theory (Kim & Lee, 1998), these quantitative or qualitative weightings (i.e., strength) can be mapped into a normalized numeric scale between 0 and 1. The weighted, directed graphs resulting from FCM approach can be analyzed using artificial neural network analysis, which can computationally simulate the dynamic of the system they represent (see Supporting information). ...
The concept of social–ecological knowledge diversity (SEKD) provides a novel way of examining coupled human–environment interactions—it acknowledges differences in knowledge, values, and beliefs of stakeholder groups within social–ecological systems (SES). Thus, understanding and measuring SEKD is an essential component of sustainable management with implications for conflict resolution, collective action and policymaking. However, methods to efficiently define and model knowledge diversity are still underdeveloped. Using a semiquantitative cognitive mapping approach, we collected and analyzed stakeholder‐specific knowledge and perceptions of the Western Baltic cod fishery to model SEKD. Results demonstrate substantial variation in perceptions across different individuals and social groups. SEKD was evident in (a) distinctive meanings attached to social factors relative to ecological factors, (b) causal relationships underlying the understanding of SES dynamics, and (c) social impacts of ecological changes on ecosystems (and vice versa). By identifying and representing knowledge‐specific disparities in SES frameworks, our model explicitly improves the understanding of human–environment interactions with implications that could help reduce conflicts and legitimize management plans. The concept of social–ecological knowledge diversity (SEKD) provides a novel way of examining coupled human–environment interactions. Using a semiquantitative cognitive mapping approach, we collected and analyzed stakeholder‐specific knowledge and perceptions of the Western Baltic cod fishery to model SEKD. SEKD was evident in (a) distinctive meanings attached to social factors relative to ecological factors, (b) causal relationships underlying the understanding of social and ecological systems dynamics, and (c) social impacts of ecological changes on ecosystems (and vice versa).
... By this evaluation, fine dependencies in causal relationships can be expressed and partial activation of concepts can be used, in contrary to the binary activation in CM. Theoretical basis of FCMs has been subsequently elaborated by many authors, (Kim & Lee, 1998), (Park & Kim, 1995), (Tsadiras & Margaritis, 1997), for example. ...
... While the preceding sections highlight the usefulness of the maps, there are also limitations. The maps as such do not provide any information on the causation (the 'why' aspect) associated with the drivers (see Kim and Lee, 1998). In this map, this has partly been circumvented through the indication of the dampening or amplifying effect the stressors have on other, related stressors (i.e., the causation). ...
Fishers, and the communities they support face a range of challenges brought on by complexity and uncertainty in their social-ecological systems (SESs). This undermines their ability to achieve sustainability whilst hampering proactive planning and decision-making. To capacitate fishers to apply risk aversion strategies at smaller scales of operation and for managers to apply inclusive management approaches such as the ecosystem approach to fisheries management (EAF), a better understanding of the relationships and interactions in marine SESs must be developed. At the same time, the EAF requires the inclusion of multiple stakeholders, disciplines and objectives into decision-making processes. Previous work in the southern Cape with fishers, identified drivers of change. Building on this previous research, and using causal mapping, fishers mapped out drivers of change in an iterative process in a problem framing exercise which also highlighted hidden drivers of change and feedback loops. To explore the relative importance of key drivers of change with participants, weighted hierarchies as well as a Bayesian Belief Network (BBN) were developed. By identifying and highlighting these hidden system interactions a more integrated systems view has been facilitated, adding to the understanding of this fishery system. Drivers identified in the weighted hierarchy were consistent with those identified in the causal maps and previous research, of interest is the relative weighting attributed to these drivers. Whereas the weighted hierarchies emphasised the political dimensions, group work already indicated the range of perceptions, reflecting the considerable uncertainties in this SES. While methodologically challenging at first, the individual approach behind the BBN construction yielded a better reflection of the diversity of views and a better balance of political, economic and climate dimensions of drivers of change. We show how, by using SDMTs, the most disenfranchised community members can engage meaningfully in a structured process. As structure is crucial to management processes, the research shows that where the appropriate groundwork, capacity building and resourcing takes place, disenfranchised stakeholders can be integrated into formal management processes; fulfilling a key requirement of an EAF.
... (ii) Possibility of susceptibility to group power dynamics in a group model-building setting cannot be ruled out; (iii) FCMs require a large amount of post-processing time [67]. (iv) The FCM-based simulations are non-real value and relative parameter estimates and lack spatial and temporal representation [60,77,78]. ...
A slew of participatory and community-demand-driven approaches have emerged in order to address the multi-dimensional nature of poverty in developing nations. The present study identifies critical factors responsible for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs) deployed for showcasing causal reasoning. It is through FCM-based simulations that the study evaluates the efficacy of existing poverty alleviation approaches, including community organisation based micro-financing, capability and social security, market-based and good governance. Our findings confirm, to some degree, the complementarity of various approaches to poverty alleviation that need to be implemented simultaneously for a comprehensive poverty alleviation drive. FCM-based simulations underscore the need for applying an integrated and multi-dimensional approach incorporating elements of various approaches for eradicating poverty, which happens to be a multi-dimensional phenomenon. Besides, the study offers policy implications for the design, management, and implementation of poverty eradication programmes. On the methodological front, the study enriches FCM literature in the areas of knowledge capture, sample adequacy, and robustness of the dynamic system model.
... (-1) identify a negative relationship, while (+1) present a positive relationship. Weights introduce by wij which describe relationship between i and j node [6,17,18,29,31,32,34,36]. Three types of relationship exist; 1. wij>0, there is a positive and direct relationship between Ci and Cj nodes. ...
... Since its first use in the social sciences over 50 years ago, CM has proved its worth in ecological management, information technology, economics, organizational behaviour and health development (Eden, Ackermann, & Cropper, 1992;Eden, Jones, & Sims, 1979;Fiol & Huff, 1992;Kim & Lee, 1998;Langfield-Smith, 1992). ...
Aims:
Describe the implementation and uses of fuzzy cognitive mapping as a constructive method for meeting the unique and rapidly evolving needs of nursing inquiry and practice.
Design:
Discussion paper.
Data sources:
Drawing on published scholarship of cognitive mapping from the fields of ecological management, information technology, economics, organizational behavior and health development, we consider how fuzzy cognitive mapping can contribute to contemporary challenges and aspirations of nursing research.
Implications for nursing:
Fuzzy cognitive mapping can generate theory, describe knowledge systems in comparable terms and inform questionnaire design and dialogue. It can help build participant-researcher partnerships, elevate marginalized voices and facilitate intercultural dialogue. As a relatively culturally safe and foundational approach in participatory research, we suggest fuzzy cognitive mapping should be used in settings of transcultural nursing, patient engagement, person and family centered care and research with marginalized populations. Fuzzy cognitive mapping is amenable to rigorous analysis and simultaneously allows for greater participation of stakeholders.
Conclusion:
In highly complex healthcare contexts, fuzzy cognitive mapping can act as a common language for defining challenges and articulating solutions identified within the nursing discipline.
Impact:
There is a need to reconcile diverse sources of knowledge to meeting the needs of nursing inquiry. Fuzzy cognitive mapping can generate theory, describe knowledge systems, facilitate dialogue and support questionnaire design. In its capacity to engage multiple perspectives in defining problems and identifying solutions, fuzzy cognitive mapping can contribute to advancing nursing research and practice. This article is protected by copyright. All rights reserved.
... Extensive discussion of the mathematical foundations of the FCM approach and specific examples of its dynamics can be found, for instance, in Kosko (1986), Kim and Lee (1998), Kok (2009), Kang et al. (2012), Lopez and Salmeron (2013), Yesil et al. (2013), Peng et al. (2015) and Vidal et al. (2015). These mathematical foundations can be summarized in Eq. (1), where A i (t+1) is the activation level of criterion C i at time t + 1; A i (t) is the activation Figure 2. Typical structure of an FCM level of criterion C i at time t; A j (t) is the activation level of criterion C j at time t; w ji is the weight of the interconnection between both criteria; and f represents a threshold activation function (Mazlack 2009). ...
Integrating sustainability into the banking activity is an increasingly necessary but extremely challenging issue currently facing financial institutions. It is therefore becoming ever more important to understand the key determinants of sustainable banking and how they inter-relate with each other. This research aims to build a cognitive map – a fuzzy cognitive map (FCM) in particular – to model, dynamically analyze and test the reciprocal influence of key factors underlying sustainable banking. FCMs have been shown to be particularly useful for handling complex decision problems characterized by lack of information or unavailable data. They constitute a methodological framework that allows for a reduction of omitted determinants – in this case, with regard to sustainable banking – and are typically able to provide a greater understanding of the cause-and-effect relationships between such determinants. We anticipate implications and practical applications for both bank managers and policymakers aiming to increase the efficiency of their decision making in the context of sustainable banking.
... The main drawbacks of FCM are:(i) the respondents' misconceptions and biases get encoded in the maps (?zesmi and ?zesmi 2004); (ii) FCM simulated results are relative and not real- value parameter estimates (Kim and Lee 1998;?zesmi and ?zesmi 2004); (iii) they do not yield data with respect to a timeframe ( Schneider et al. 1998;?zesmi and ?zesmi 2004); and (iv) require a large amount of post-processing time ( Diniz et al. 2015). ...
... The mathematical foundations and practical examples of the FCM approach can be found in previous literature (see, for example, Kosko 1986;Kim and Lee 1998;Kok 2009;Papageorgiou and Salmeron 2013;Ferreira 2016;Ribeiro et al. 2017). Still, as Mazlack (2009) notes, these foundations can be summarized according to ...
Because the perceived ethics of a banking institution can affect its reputation, concern over ethical practices in the banking sector is rapidly increasing. The alignment of such practices with daily operations, however, requires dealing with a wide range of variables, tangible or intangible, and constitutes a notoriously difficult endeavor. Still, due to the rapidly changing economic environment and current sharp competition in the banking industry, a better understanding of this alignment can help bank managers and other key players enhance value creation through more informed decisions, contributing to stronger integration of ethical practices in the banks’ daily activities. This paper proposes the use of fuzzy cognitive maps (FCMs) to analyze the dynamics behind ethical banking practices. Grounded on intensive group meetings with a panel of senior executives from the banking industry, the result is a well-informed process-oriented framework that sheds light on the manner in which ethical practices interrelate with each other. Implications, advantages and shortcomings of our proposal are also discussed.
... It must be mentioned that all the values in the graph are fuzzy. Causality between concepts allows degrees of causality and not the usual binary logic, so the weights of the interconnections belong to the interval [-1,1] (Kim, 1998). Fuzzy Cognitive Map describes a system in a one-layer network whose nodes can be assigned concept meanings and the interconnection weights represent relationships between these concepts. ...
This paper investigates the implementation of a hybrid methodology, which combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for the modeling of the supervisor of Large Scale Systems. The description and the construction of Fuzzy Cognitive Map will be extensively examined and it will be proposed a model for the supervisor. There is an oncoming need for more autonomous and intelligent systems, especially in Large Scale Systems and the application of Fuzzy Cognitive Map for the modeling of the Supervisor may contribute in the development of more autonomous systems.
... Cognitive mapping became an even more powerful tool with the development of fuzzy cognitive maps (Kosko 1986(Kosko , 1992, which have been extensively applied to a variety of different contexts and decision problems, sharing the common trait of complexity (e.g. Kim, Lee 1998;Stylios, Groumpos 1999;Tsadiras et al. 2003;Carvalho 2013;Ferreira et al. 2015a). In this type of maps, the relationships between criteria can be represented by positive and negative causality; the intensity of which is then translated into a number which can vary from -1 to 1. Specifically, all the values in the map can be fuzzy and, therefore, each concept has a state value A i that can be a fuzzy value in the range [0, 1] or a bivalent logic in {0, 1}. ...
Understanding customer loyalty has been a growing concern for the services industry. In a context of increasing competitive pressures, such loyalty is seen as a key element in service companies’ success. Maintaining customer loyalty and identifying its underlying factors, however, are recognizably difficult to do. Grounded on the use of cognitive mapping techniques, this paper proposes a knowledge-based framework for the identification of the key determinants of customer loyalty, and the relationships among them. A step-by-step guide to the development of such a framework is presented, and illustrated through a practical application in the banking context. The resulting findings are supportive of the applicability of such methods for understanding customer loyalty, and the improvement of long-term relationships with customers. They are furthermore indicative of new ways in which knowledge can be incorporated into management activities to improve service outcomes. Some managerial implications of our contribution and avenues for future research are also reported.
First published online: 20 Feb 2017
... The main drawbacks of FCMs are: (i) the respondents' fallacies as misconceptions and biases get encoded in the maps (Özesmi and Özesmi 2004); (ii) FCM simulated results are relative and not real-value parameter estimates (Kim and Lee 1998;Özesmi and Özesmi 2004); (iii) they do not yield data with respect to a timeframe (Schneider et al. 1998;Özesmi and Özesmi 2004); and (iv) require a large amount of post-processing time (Diniz et al. 2015). ...
Drought is among the most dreaded threats as far as natural disasters are concerned wielding, as it does, a significant impact on ecosystems, people’s livelihoods, and the socio-economic development of a country. A significantly large geographic area of India happens to be drought prone. In order to understand people’s response to the impacts of drought and their coping strategies, it is crucial to understand their perceptions. Studies investigating community perceptions relevant to drought impacts and concomitant adaptive behaviours are rare in India. This paper documents communities’ perceptions of impacts of drought on their livelihood assets and adaptation practices. It does this with the help of the fuzzy cognitive mapping approach in the Mahabubnagar district of India’s Telangana state. In order to develop pathways for drought resilient livelihoods we ran simulations for future drought scenarios with various bundles of adaptation strategies enabling us to evaluate their effectiveness in providing resilience against drought. The study also tested the suitability of various activation rules and transformation functions, used for running simulations. Incorporating stakeholders’ perceptions, knowledge and beliefs about impacts of droughts, and engaging them in the process of developing drought resilient livelihoods is expected to fine-tune the drought related policy-making.
... In technical terms, this means that there are three different types of relationships between nodes: (1) negative causality (W ij < 0), where an increase/decrease in the value of C i leads to an decrease/increase in the value of C j ; (2) null causality (W ij = 0), which takes place when there is no relationship between C i and C j ; and (3) positive causality (W ij > 0), where an increase/decrease in the value of C i leads to an increase/decrease in the value of C j (cf. Kim, Lee 1998;Mazlack 2009;Kok 2009;Salmeron 2009;yaman, Polat 2009). ...
Previous research has indicated that residents’ satisfaction with neighborhood conditions helps shape attitudes and has a high impact on residential valuations. This paper reports on research that sought to analyze the relationship between neighborhood characteristics and residents’ degree of satisfaction. Based on the construction of a fuzzy cognitive map (FCM), which involved residents from several highand low-quality neighborhoods in the Central-West region of Portugal, a framework that adds value to the way key determinants of neighborhood satisfaction are identified is proposed. Because FCMs allow the understanding of the cause-and-effect relationships between factors to be improved, this framework shows that for satisfaction with the neighborhood to increase, more attention needs to be paid to positive attitudes toward subjective variables that interfere with residents’ satisfaction. The results presented can provide relevant information for the effective and efficient planning and development of residential environments. Strengths and weaknesses of this proposal are also discussed.
... FCM has been used as a knowledge acquisition scheme [25]. It displays a thinking system through a graph showing a cause and effect. ...
Turkey has experienced a major wave of migration since the early 1950s. Although many studies have tried to investigate how social dynamics and identities play a role in the migration phenomenon in urban areas, none of them have analysed this through a model that allows to present perception of migrants and the phenomenon of migration from the point of view of social groups at a conceptual and relational level. This study conducted in Gebze proposes to analyse FCMs based on modelling position and perception that shows how migrants locate one another in the city and the migration phenomenon. The findings of this study suggest that since experiences and perceptions differ according to social categories, social inequalities caused by and/or leading to migration become visible and more comprehensive from the perspective of different social categories of migrants.
... As the literature indicates (cf. Ferreira et al., 2015;Kim & Lee, 1998;Kok, 2009;Mazlack, 2009;Salmeron, 2009;Yaman & Polat, 2009), all the values in a FCM can be fuzzy, such that a state value A i for each variable considered can take on a fuzzy value in the range between [0, 1] (or at least follow a bivalent logic in {0, 1}). The linkages, in turn, can take on three different types of causality: (1) negative (W ij b 0), when an increase (decrease) in the value of C i leads to a decrease (increase) in the value of C j ; (2) null (W ij = 0), when no relationship between the variables exists; and (3) positive (W ij N 0), when an increase (decrease) in the value of C i leads to an increase (decrease) in the value of C j . ...
This study proposes the use of fuzzy cognitive maps (FCMs) in qualitative comparative analysis (QCA) applications to enhance the selection of independent variables in the QCA framework. QCA techniques hold great potential to identify the causal models that exist among different but comparable cases. Due to the complexity of causality issues, however, such techniques may not be able to uncover the “true” causal foundation of a given phenomenon. FCMs typically offer a fuller view of the cause-and-effect relationships between variables, thus allowing for a better understanding of their behavior; for instance, the manner in which variables relate to each other, or the measure of their intensity. This study thus proposes that such maps can be a useful support in the selection of independent variables for a QCA model, and provides specific guidelines and an illustrative example of how to integrate FCMs in QCA applications.
... When two variables represented opposite directions of the same concept (i.e. dam construction and dam removal) the more prevalent variable was retained and the other variable was renamed, with the polarity of the interactions reversed, in keeping with accepted practices (Kim and Lee, 1998). The interactions strengths between variables were then scored, with high interactions scored as 0.75, medium as 0.5, and low as 0.25 (Harary et al. 1965). ...
... A Fuzzy Cognitive Map (FCM) is a fuzzy weighted network used to model and analyze systems by presenting the causal relationships among system's components [7]. This technique has four advantages in analyzing complex systems: (a) it models complex problems in a simple and understandable way, (b) it is flexible in system analysis and design and has the ability to deal with fuzzy information, (c) it can represent all possible causal relationships between components of a given problem and (d) FCM inferences are carried out by numerical calculations instead of symbolic deductions [3,4,11]. ...
In this paper a new algorithm for Fuzzy Cognitive Maps learning is introduced. The proposed approach is based on the cultural algorithm and it is used to build the weight matrices that allow the Fuzzy Cognitive Map algorithm to find the final steady states. A Fuzzy Cognitive Map (FCM) is a fuzzy signed directed graph with feedback and models complex systems as a collection of concepts and causal relations between concepts. An FCM can be constructed by using experts' knowledge or historical data. In this paper we have developed an automated method FCM learning which uses a type of evolutionary algorithm known as a cultural algorithm. We explain the algorithm and demonstrate its performance advantages.
... However, a FCM 184 substitutes these signs by a fuzzy value between -1 and +1 where the zero 185 value indicates the absence of causality. Secondly, it involves feedback, where the effect of change in a concept node may affect other concept nodes (Kim 187 & Lee, 1998;Papageorgiou & Salmeron, 2014). 188 In addition, one assumes that the decision makers can construct an ac- The survey has been divided into three questionnaires, product, use and 272 manufacturing. ...
Several studies have been developed implementing TRIZ (Russian acronym of Theory of Inventive Problem Solving) for eco-innovative design tasks, establishing a link between eco-efficiency and the Inventive Principles and the Contradiction Matrix. However, very few works have linked TRIZ evolution trends and eco-design. This paper presents an innovative methodology to help designers to predict technological evolutions for more environmentally friendly products. The main novelty of our proposal is the use of Fuzzy Cognitive Maps (FCMs) to analyse, identify and quantify the relationship between the strategies of the Eco-Design Strategy Wheel and the TRIZ evolution trends. This methodology has been applied to the Spanish ceramic industry using data from a survey to their business leaders. Results show evolution trends of ceramic products focused on Material, Design Process and Geometry are more environmentally friendly. In contrast, evolution trends included in the category Aesthetics are harmful for the environment. The methodology proposed can be applied for greener product design and technological forecasting in other industries.
... We treated each pressure"s conceptual scheme separately to build an adjacency matrix and subsequently combined all adjacency matrices by matrix addition to construct an overall adjacency matrix of the total system including all pressures. Conflicting connections with opposite signs (that would decrease total causal relationship during matrix addition) that resulted from different logical structure of few conceptual schemes (Zhang & Chen 1988) were corrected by switching signs, an operation that does not change system behavior (Kim & Lee 1998). After total matrix addition, each element in the summed overall adjacency matrix was normalized by the number of conceptual schemes included (Kosko 1992b). ...
European rivers have been altered by means of changing their morphology (straightening and canalisation, disconnecting channels from flood plains, occupying riparian lands, building dams, weirs, bank reinforcements, etc.) to facilitate agriculture and urbanisation, to enable energy production and protection against flooding. Also, water has been abstracted from rivers and their natural flow regime to be used as a resource for irrigation and to supply urban and industrial needs. All these human activities have damaged fluvial habitats and have had severe and significant impacts on the status of the aquatic ecosystems. These hydromorphological (HYMO) pressures are the most commonly occurring pressures in European rivers, lakes and transitional waters, affecting more than 40 % of all river and transitional water bodies. This report is a bibliographic review concerning the effects of HYMO pressures on hydromorphological processes and variables resulting from both degradation and restoration. Based on this review, we aim to identify the most significant HYMO pressures as well as relevant hydromorphological effects of the different pressure types on fluvial systems across spatial and temporal scales and in particular those that have a significant impact on aquatic biological elements. This review further provides a tool to identify gaps in present HYMO knowledge, which is needed to improve our understanding of the mechanisms that control degradation-restoration processes. To illustrate relevant gaps conceptual schemes have been developed of the interactions between HYMO pressures, the main processes affected and the resulting quantified changes on HYMO variables. Referenced citation frequencies were used to relate the different elements of each scheme.
Hydromorphological pressures were grouped into the following types:
1. Hydrological regime pressures, including water abstraction and flow regulation
2. River fragmentation pressures
3. Morphological alteration pressures
4. Other elements and processes affected (physico-chemical)
The pressure effects were analyzed separately for each hydromorphological pressure by developing a diagram showing its direct effects on the processes and on the state variables, but in turn also the induced process changes with respect to HYMO variables. The following main HYMO processes were considered:
- Water flow dynamics
- Sediment dynamics (sediment entrainment, transport, deposition, armouring)
- Bank dynamics (bank erosion & failure, stabilization)
- Vegetation dynamics (vegetation encroachment, uprooting, recruitment)
- Large wood dynamics (entrainment, transport, deposition)
- Aquifer dynamics (aquifer recharge, discharge)
The quantitative variables provide the measures of the intensity of the processes and are useful to monitor river changes and to evaluate pressure effects. Whilst the biotic communities typically respond to the status of the variables, sustainable and successful river restoration should address the processes behind which determine the variables’ state. Therefore, all pressure specific conceptual schemes developed have been incorporated into one single effect matrix and analyzed using Fuzzy Logic Cognitive Maps (FCM) to identify the most relevant HYMO pressures as well as the most affected processes and variables. FCMs are based on graph theory models of the causal relationships between defined variables and can be viewed as a combination of fuzzy logic and artificial neural networks. FCMs qualitatively incorporate expert knowledge to explore implications for ecosystem management.
The overall hydromorphological pressure-impact model very well depicted the present status of processes and variables corresponding to the commonly observed hydromorphological conditions in altered river systems. Dynamics of flowing water emerged as the most important hydromorphological process. This was not surprising, but it still underlines the necessity to rehabilitate a more natural flow regime to improve the hydromorphological status of the rivers and the related biological communities.
Vegetation encroachment emerged as second most important process which seems well in line with the natural river typology developed in WP2 and the identified importance of riparian vegetation in shaping riverine landscapes. The next important processes were all related to sediments underlining the key role of bedload transport and sediment dynamics in forming fluvial habitats.
To provide further guidance to river restoration, the effects of single pressure removals have been analyzed by simulating the system behavior in response to various management options, i.e. management simulations. Removing one of the pressures completely would cause on average a change of 57% of all hydromorphological variables considered (ranging between 31% for improving vertical connectivity and 68% for large dam removal). These findings, however, did not only allow identifying the main pressures and most important processes, they also pose major challenges on identifying key variables and variables’ changes which significantly affect the biotic response. Major knowledge gaps comprise the interplay between synchronously and asynchronously responding variables and the assessment of the finally resulting status of the hydromorphological variables in different river types. Closely related to that, assessing the resulting potential effects on biota as well as differential responses of different taxa to various variable changes and variable states provide additional challenges.
... The FCM technique is used to model and analyze the behavior of dynamic and complex systems [34]. The FCM technique can handle fuzzy information and uncertainty in modeling and analyzing a system [15,21,64]. The result of analyzing a system with the FCM technique is a network which includes causal relationships between components of the system. ...
In this paper, a new automated Fuzzy Cognitive Maps (FCMs) learning algorithm is developed to generate FCMs from historical data. Automated FCM learning algorithms are used to model and analyze systems which are very complex and cannot be handled by experts’ knowledge. The algorithm developed in this paper is based on the Imperialist Competitive Algorithm for global optimization and is called the Imperialist Competitive Learning Algorithm (ICLA). The ICLA divides the search space into several sections. It extracts the best knowledge from each section and follows a procedure to avoid local optima alongside rapid learning. Experiments have been conducted to compare the ICLA with other well-known FCM learning algorithms. The results show that in most cases, the ICLA performs better for learning FCMs in terms of solution accuracy and execution time. The testing results show clearly that the ICLA is a robust, fast and accurate FCM learning algorithm.
The purpose of this study is to build a cognitive model of the system–industrial complex of the Southern Federal District of Russia. The Southern Federal District is a region in the south of Russia, which includes the regions of Rostov, Volgograd, Astrakhan, and Krasnodar; the Republics of Adygea, Kalmykia, and Crimea; and the federal city of Sevastopol. The object of the study was the industrial complex of Southern Federal District, which ranks 6th in terms of the share of manufacturing among the federal districts. The study was conducted at the Southern Federal University, which is located in the Southern Federal District of Russia. This article discusses the use of the cognitive modeling method, which allows us to determine the degree of system stability and the direction of system development under varying degrees of influence of external factors. This method is used to build forecasts of the development of poorly structured socioeconomic systems. The cognitive modeling method made it possible to predict one of the scenarios for the development of the industrial complex of the Southern region of the Russian Federation. For the subject under study, indicative, controlling, and regulating peaks have been identified, but the difficulty of forecasting is noted due to the lack of a general program for the industrial complex of the federal district. The article presents scenarios of industrial development of the Rostov and Krasnodar regions as the most industrially developed regions in the Southern Federal District. Cognitive modeling allows building scenarios of development of the studied systems of regions by means of impulse influence, that is, when one vertex affects another vertex. The modeling results made it possible to build a cognitive map of the industrial complex of the Southern Federal District. This map showed that in the case of impulse impact on the industrial complex, it is necessary to strengthen regulatory measures on the part of the state.
Fuzzy cognitive maps are studied from statistical standpoint. An analogy between these maps and linear regression and logistic regression models is drawn. Practical examples are also provided.
The increasing use of information technology in enterprises’ daily operations has led to multiple innovative ways to run a business, including electronic commerce (hereafter, e-commerce). However, firms with fewer resources, such as small and medium-sized enterprises (SMEs), are more reluctant to use electronic channels during transactions. This aversion to contemporary business models is a result of these companies’ lack of knowledge and capabilities regarding e-commerce. To improve their businesses, SMEs’ managers and decision makers could benefit from a methodological framework that fosters a deeper understanding of the determinants of e-commerce. This study sought to explore the use of fuzzy cognitive mapping to address this need. The results are grounded in the knowledge and experience of a panel of experts in e-commerce. The fuzzy cognitive map (FCM) developed shows that entrepreneur profile, market, operational management, marketing and promotions, website and digital platform, and products present the highest centrality indices as determinants of SME e-commerce. The findings offer a better understanding of the cause-and-effect relationships between these determinants. The advantages, limitations, and shortcomings of our constructivist proposal are also discussed.
First published online 10 April 2019
Resilience is an increasingly important concept in current socioeconomic landscapes. Due to the competitive global context in which we live, this trend is particularly noticeable in small and medium‐sized enterprises (SMEs). Due to their limited resources and capabilities, these firms are exposed to unfavourable scenarios that can threaten their stability, viability, and development (i.e., their resilience). Thus, identifying the determinants of SME resilience and their respective cause‐and‐effect relationships is a vital endeavour because these companies' resilience involves a wide variety of conceptual or theoretical issues that need to be understood more fully. This study proposes the creation of a fuzzy cognitive map as a novel way to analyse the determinants of SME resilience. The fuzzy cognitive map was developed based on the insights obtained during two intensive group meetings with a panel of SME managers and entrepreneurs. The resulting well‐informed, process‐oriented framework contains the determinants that need to be considered in this research context. The static and dynamic analyses carried out produced an improved understanding of the cause‐and‐effect relationships between determinants of SME resilience, which facilitates better strategic planning by these firms' managers. The practical implications, advantages, and limitations of the proposed approach are also discussed.
Credit to personal consumption is an important activity of the financial system and
crucial to the socio-economic development of a country. It is important, therefore, that the
methods and techniques used to evaluate consumer credit risk be as efficient and informative as possible, in order to strengthen decisions to approve or reject credit and promote sustainable economic growth. This study aims to create a multiple criteria expert system which integrates cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH) to create a complementary framework for consumer credit risk assessment. The results show that this integrated approach allows the evaluation process of consumer credit risk to be more informed and transparent, providing value for the evaluation processes of this type of credit application as a result of the privileged contact established with a panel of credit analysts. Limitations and managerial implications are also discussed.
Credit to personal consumption is an important activity of the financial system and crucial to the socio-economic development of a country. It is important, therefore, that the methods and techniques used to evaluate consumer credit risk should be as efficient and informative as possible, in order to strengthen decisions to approve or reject credit and promote sustainable economic growth. This study aims to create a multiple criteria expert system which integrates cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH) to create a complementary framework for consumer credit risk assessment. The results show that this integrated approach allows the evaluation process of consumer credit risk to be more informed and transparent, providing value for the evaluation processes of this type of credit application as a result of the privileged contact established with a panel of credit analysts. Advantages, limitations and managerial implications are also discussed.
The recent economic crisis led to significant changes in the real estate market; one of which was a shift toward home rental (rather than buying). Real estate investors have an important role in the growth of the rental market. However, there are often hindrances to investing for residential rental purposes. In order to overcome these barriers, they first need to be identified and understood. With this in mind, the main focus of this investigation was the creation of a conceptual model, through fuzzy cognitive mapping, to identify and understand the cause-and-effect relationships between the factors that represent an obstacle to real estate investments for residential rental purposes. The results show that cognitive maps can be of great use for the structuring of complex decision problems, minimizing the number of factors left out of the decision making process. In particular, the tenant risk behavior, property location and associated costs (for the owner) were identified as the main obstacles to real estate investment rental propose. The practical implications of the model, as well as the advantages and limitations of the process followed, are also discussed.
As interest in sustainability-related issues has increased over recent years, so too has urban sustainability risen to the fore, in academic, practitioner, and policymaking circles alike. Urban sustainability requires a balance between environmental concerns, the economy, and social development in urban areas. However, over the years, there has been an exponential increase in urban density, accompanied by increased economic activity and high levels of consumption, which have hindered urban planning and made the sustainable management of urban areas more difficult. It has therefore become increasingly necessary to combine the interests of the various stakeholders involved in – or affected by – urban planning measures, in order to achieve a balance between their needs, those of the environment and future generations, and the need for economic development. Sustainability evaluation models can in this sense be considered a baseline condition for sustainable development. However, most existing evaluation systems present limitations in terms of criteria identification and the calculation of the respective trade-offs. To address these issues, the current study aims to combine cognitive mapping and the Analytic Hierarchy Process (AHP) to prioritize the determinants of sustainable development in urban areas. The advantages and limitations of our proposal are also analyzed.
In Complex Large Scale Systems there is an oncoming need for more autonomous and intelligent systems, new methodologies from discipline research areas have been proposed. A general formulation for the Overall Control Problem of Complex Systems is presented. Then, the use of a hybrid methodology, which combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for the modeling Supervisory Complex Systems, using is investigated. The description and the construction of Fuzzy Cognitive Map is examined and a model for the supervisor is proposed.
Risk analysis of residential real estate investments requires careful analysis of certain variables (or determinants). Because real estate is a key sector for economic and social development, this risk analysis is seen as critical in supporting decision processes relating to buying or selling residential properties, partly due to the pressures caused by the current economic environment. This study aims to develop a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping. This fuzzy model allows cause-and-effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions. The results show that the use of cognitive maps reduces the number of omitted criteria and favors learning with regard to how the criteria relate to each other, holding great potential and versatility in structuring complex decision problems. Practical implications, strengths and weaknesses of our proposal are discussed.
The performance evaluation of health, safety and environment management system (HSE-MS) is considered to be an effective way to eliminate out dated measures and help managers adopt proper rectification measures. The objective of this paper is to design a weight distribution model for HSE-MS performance evaluation, the importance of which stems from the current lack of integrated approaches for interpreting and ranking HSE-MS performance evaluation elements. Initially, Fuzzy Cognitive Maps (FCM) is adopted to illustrate the direct and indirect effects of HSE-MS elements on system performance indicators, and the results of FCM are used to develop leading factors helpful for decision making in an intensive management system. Then, the weight distribution from FCM is amended by Relative Degree Analysis (RDA), the aim of which is to combine the advantages of quantitative and qualitative knowledge-driven methods. Finally, the level of HSE-MS performance is obtained and analyzed. The whole performance evaluation framework highlights the potential correlations of evaluation elements as well as expert opinions, which will improve the reasonability of the HSE-MS performance evaluation.
Different pressures often co‐occur in rivers and act simultaneously on important processes and variables. This complicates the diagnosis of hydromorphological alterations and hampers the design of effective restoration measures.
Here, we present a conceptual meta‐analysis that aims at identifying the most relevant hydromorphological processes and variables controlling ecological degradation and restoration. For that purpose, we used fuzzy cognitive mapping based on conceptual schemes that were created according to 675 scientific peer‐reviewed river hydromorphology studies.
A model generated from this approach predicts responses that are consistent with common understanding of the direct interactions between hydromorphological pressures, processes and variables. However, it also leads to new knowledge beyond traditional hydromorphological models by dealing with the complex interactions of hydromorphology, vegetation, water chemistry and thermal regime.
Water flow dynamics appeared as the most important of all hydromorphological processes affected by simultaneously interacting pressures. Relevant processes such as vegetation encroachment and sediment entrainment are closely linked to water flow.
Synthesis and applications . Our results demonstrate the relevance of natural flow regime rehabilitation for river management. Hence, we suggest focusing primarily on rehabilitating the natural flow regime before carrying out extensive habitat restoration works. This challenging target in river rehabilitation could strongly increase the success of additional habitat restoration.
Price and residential housing attributes have long been identified as key determinants of home sales and, as such, they can explain time-on-the-market (TOM). It is acknowledged, however, that there are other factors (or determinants) that influence home sales and TOM, which are of great importance but seldom taken into account in the appraisal process of residential real estate. Based on the use of fuzzy cognitive mapping, we propose a framework that adds value to the way that key determinants of housing sales and TOM are identified. This framework is the result of a process involving several residential real estate experts (i.e. appraisers and realtors), and follows a constructivist approach. Our findings suggest that the use of fuzzy cognitive maps (FCMs) allows the number of omitted determinants to be reduced and the understanding of the relationships between them to be improved. The strengths and weaknesses of our methodological framework are also discussed.
This paper presents the application of a Fuzzy Cognitive Map (FCM) based theoretical framework and its associated modeling and simulation tool to StrategyMaps (SMs). Existing limitations of SMs are presented in a literature survey. The need for scenario based SMs with inherited ability to change scenarios dynamically as well as the missing element of time are highlighted and discussed upon. FCMs are presented as an alternative to overcome these shortfalls with the introduction of fuzziness in their weights and the robust calculation mechanism. An FCM tool is presented that allows simulation of SMs as well as interconnection of nodes (performance measures) in different SMs which enable the creation of SM hierarchies. An augmented FCM calculation mechanism that allows this type of interlinking is also presented. The resulting methodology and tool are applied to two Banks and the results of these case studies are presented.
This paper is a journey around causality, imperfect causality, causal models and experiments for testing hypothesis about what causality is, with special attention to imperfect causality. Causal relations are compared with logic relations and analogies and differences are highlighted. Classical properties of causality are described and one characteristic more is added: causes, effects and the cause-effect links usually are qualified by different degrees of strength. Causal sentences automatically recovered from texts show this. In daily life, imperfect causality has an extensive role in causal decision-making. Bayes Nets offer an appropriate model to characterize causality in terms of conditional probabilities, explaining not only how choices are made but also how to learn new causal squemes based on the previously specified. Psychological experiments seem to support this view. But Bayes Nets have an Achilles hell: if the names labeling nodes are vague in meaning, the probability cannot be specified in an exact way. Fuzzy logic offers models to deals with vagueness in language. Kosko fuzzy cognitive maps provide the classical way to address fuzzy causalility. Other less relevant models to manage imperfect causality are proposed, but fuzzy people still lacks of a comprehensive batterie of examples to test those models about how fuzzy causality works. We provide a program that retrieves causal and conditional causal sentences from texts and authomatically depicts a graph representing causal concepts as well as the links between them, including fuzzy quantifiers and semantic hedges modifying nodes and links. Get these mechanisms can provide a benchmark to test hyphotesis about what is fuzzy causality, contributing to improve the current models.
Using fuzzy cognitive mapping, this study aims to create a holistic framework whereby the determinants of bank branch service quality and their cause-and-effect relationships can be identified and dynamically analyzed. The methodology is applied using a group of experts from the banking industry in Portugal. Our results not only indicate the applicability and usefulness of the proposed approach, but identify human resource characteristics (which include collaborators’ personal and professional training) and management team technical skills as particularly relevant driving forces of bank branch service quality. The proposal holds great potential for the operational planning and improvement of bank branch service quality, which is a prime concern for bank administrators, bank branch collaborators, and society at large. Advantages and shortcomings of the framework are also reported.
Je popsána metodika výzkumu mentálních a kognitivních map, dosažené výsledky a další směry výzkumu této problematiky.
*********cite as: Zelenka, J., Mls, K., Šípek, J., Štyrský, J., Bodnárová, A., Pásková, M., Gavalec, M., Lehmannová, Z., Ježek, B., Vaněk, J., Janečka, P., Vydra, L., Poděbradský, P., Pilařová, Z., Franěk, M. Výzkum kognitivních a mentálních map. Hradec Králové : Univerzita Hradec Králové, 2008. 197s. ISBN: 978-80-7041-323-4
To complement and augment the present methods used for information requirements analysis, the application of cognitive mapping is introduced. The proposed technique, which involves there cognition of cause and effect relationships, appears to provide three benefits. It aids in the identification of irrelevant data. It can be used to evaluate the factors that affect a given class of decisions. And, most importantly, it enhances the overall understanding of a decision maker's environment, particularly when it is ill-structured. These observations are supported by a real world application of the approach to the evaluation of the performance of insurance claim representatives.
Two of the main views of learning are considered: stimulus-response association theory and field-cognition theory. Two aspects of machine learning are then looked at: concept learning and rule induction. The ID3 algorithm and its experimental evaluation are discussed.
This is a general guide to expert systems written specifically for the reader without a computer science background. Contents: Introduction; Introduction to expert systems; Expert system tools; Building an expert system; Difficulties with expert system development; Expert systems in the marketplace; Expert systems and tools; Glossary of expert system terms; References; Author index; Subject index.
Fuzzy cognitive maps (FCMs) are fuzzy-graph structures for representing causal reasoning. Their fuzziness allows hazy degrees of causality between hazy causal objects (concepts). Their graph structure allows systematic causal propagation, in particular forward and backward chaining, and it allows knowledge bases to be grown by connecting different FCMs. FCMs are especially applicable to soft knowledge domains and several example FCMs are given. Causality is represented as a fuzzy relation on causal concepts. A fuzzy causal algebra for governing causal propagation on FCMs is developed. FCM matrix representation and matrix operations are presented in the Appendix.
The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.
Management of uncertainty is an intrinsically important issue in the design of expert systems because much of the information in the knowledge base of a typical expert system is imprecise, incomplete or not totally reliable.In the existing expert systems, uncertainty is dealt with through a combination of predicate logic and probability-based methods. A serious shortcoming of these methods is that they are not capable of coming to grips with the pervasive fuzziness of information in the knowledge base, and, as a result, are mostly ad hoc in nature. An alternative approach to the management of uncertainty which is suggested in this paper is based on the use of fuzzy logic, which is the logic underlying approximate or, equivalently, fuzzy reasoning. A feature of fuzzy logic which is of particular importance to the management of uncertainty in expert systems is that it provides a systematic framework for dealing with fuzzy quantifiers, e.g., most, many, few, not very many, almost all, infrequently, about 0.8, etc. In this way, fuzzy logic subsumes both predicate logic and probability theory, and makes it possible to deal with different types of uncertainty within a single conceptual framework.In fuzzy logic, the deduction of a conclusion from a set of premises is reduced, in general, to the solution of a nonlinear program through the application of projection and extension principles. This approach to deduction leads to various basic syllogisms which may be used as rules of combination of evidence in expert systems. Among syllogisms of this type which are discussed in this paper are the intersection/product syllogism, the generalized modus ponens, the consequent conjunction syllogism, and the major-premise reversibility rule.
Complex social systems are difficult to represent. Relationships between social forces demand feedback. For example, the causal connection between commodity price and consumer demand is a feedback system. Price increase tends to decrease demand for some commodities. On the other hand, an increased demand tends to elevate price. A stable system settles into equilibrium. A dynamic system is needed to model shifts in equilibrium brought about by changes in the causal environment. The knowledge-based expert system lacks the intrinsic structure for modeling these effects. Internally, all expert systems depend on these representations. Some attempt to simulate unrestricted graphs with virtual registers and loop counters. The result is a semantic gap between the internal representation of the social system and the social system itself. This article presents the Fuzzy Cognitive Map (FCM) alternative to the expert system. We first describe the FCM. We then diagram several social systems. Finally, we show a method for combining credibility-weighted FCMs to achieve a single global knowledge base.
The objective of this paper is to apply fuzzy cognitive map (FCM)-related techniques to (1) extract causal knowledge from a specific problem-domain, (2) construct a hierarchical knowledge base, and (3) perform a bi-directional inference. The causal knowledge base built by FCM can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if–then) knowledge base. Based on the causal knowledge base, we can break down a given decision problem into a multi-leveled one. Then bi-directional (downward or upward) inference can be applied to the multi-leveled problem to find a more robust solution. We applied our method to a stock investment analysis problem which is typical of highly unstructured problems in OR/MS fields. © 1997 by John Wiley & Sons, Ltd.
Fuzzy cognitive maps (FCMs) represent a means of fuzzy causal knowledge processing, using the net rather than the traditional tree knowledge representation. The FCM approach allows various knowledge bases to be combined. Similarities between the FCMs and signal flow graphs (SFGs) are pointed out and the inference process used in FCMs is compared in parallel with a fixed point iterative solution of the equations describing the SFG. Then, applications to qualitative circuit analysis are discussed for a class of feedback amplifiers and general active RLC circuits, using a combination of the SFG and FCM concepts. Several examples are given.< >
Using a compound-valued logic, a logical architecture is introduced for representing fuzzy cognitive maps and for modeling knowledge acquisition in adaptive bidirectional associative memories. The excitatory, neutral, and inhibitory values of causal relations provide an effective paradigm for knowledge acquisition and processing. The main contribution is a NPN (negative-positive-neutral) calculus that is used as a logical inference engine.< >
A study on the development of multiple expert's knowledge combining algorithm by using fuzzy cognitive map
- K C Lee
- S C Chu
- H S Kim
K.C. Lee, S.C. Chu and H.S. Kim, A study on the development of multiple expert's knowledge combining algorithm by using fuzzy cognitive map, J. Korean Oper. Res. Management Sci. Soc. 19 (1994) 17-40 (in Korean).
Fuzzy cognitive map-based knowledge acquisition algorithm: applications to stock investment analysis
- K C Lee
- S C Chu
- H S Kim
K.C. Lee, S.C. Chu and H.S. Kim, Fuzzy cognitive map-based knowledge acquisition algorithm: applications to stock investment analysis, in: W. Cheung, Ed., Selected Essays on Decision Science (Department of Decision Science and Managerial Economics, The Chinese University of Hong Kong, 1993) 129-142.
Fuzzy cognitive mapbased knowledge acquisition algorithm: applications to stock investment analysis
- Lee
A study on the development of multiple expert's knowledge combining algorithm by using fuzzy cognitive map
- Lee