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Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process w...
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... is worth mentioning that the confusion matrix is used as the measure of accuracy to evaluate the performances of the binary classification model by the GMDH algorithm. The basic form of a confusion matrix is shown in Figure 3, and Equations (8) and (9) indicate the mathematical relations of accuracy and error. ...
Context 2
... is worth mentioning that the confusion matrix is used as the measure of accuracy to evaluate the performances of the binary classification model by the GMDH algorithm. The basic form of a confusion matrix is shown in Figure 3, and Equations (8) and (9) indicate the mathematical relations of accuracy and error. ...
Context 3
... is worth mentioning that the confusion matrix is used as the measure of accuracy to evaluate the performances of the binary classification model by the GMDH algorithm. The basic form of a confusion matrix is shown in Figure 3, and Equations (8) and (9) indicate the mathematical relations of accuracy and error. ...
Context 4
... is worth mentioning that the confusion matrix is used as the measure of accuracy to evaluate the performances of the binary classification model by the GMDH algorithm. The basic form of a confusion matrix is shown in Figure 3, and Equations (8) and (9) indicate the mathematical relations of accuracy and error. ...
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Citations
... A case study utilizing fuzzy rule induction and CMC-which is improved by deep learning networks-is examined in order to gain more accurate stochastic insights on the evolution of the pandemic. Fuzzy rule induction approaches are used in conjunction with a deep learning-based CMC, as opposed to relying solely on uniform and uncomplicated assumptions for an MC [17]. Throughout this work, a novel bio-inspired metaheuristic simulates the transmission and infection of healthy individuals by the coronavirus. ...
SARS-CoV-2, a novel coronavirus discovered in Wuhan, China is spreading quickly and has a high incidence rate around the globe. As a result, everyone on the planet is having difficulty adjusting to the effects of Corona and is unable to foresee the devastation and disaster caused by COVID-19. In this work, we predict the survival status of patients infected with coronavirus using three distinct machine learning (ML) techniques: Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). We also assess the classification performances of these algorithms. Here, we put out a hybrid model and evaluated it against the three previously discussed machine learning techniques. The outcomes demonstrated the 97.85% prediction accuracy of our suggested hybrid model. Aside from our suggested hybrid model, the random forest machine learning method demonstrated the highest accuracy of 94.62% among the three. Nonetheless, the prediction accuracy of the hybrid model outperforms that of the random forest and is significantly better than that of the other three ML techniques. The classification performances were assessed using the F-score, sensitivity, specificity, and precision metrics. Using 10-fold cross-validation, ROC assessments and confusion matrices produced by these machine learning algorithms were provided and examined. to assess the effectiveness of the classification. These machine learning algorithms' ROC assessments and confusion matrices are shown and examined by 10-fold cross-validation.
... Regresyon modelinde ortalama günlük nem oranı %77,9 vaka sayılarını olumlu etkilerken, günlük hava sıcaklığının maximum 15,4 ° C'ye düşmesi vaka sayılarını olumsuz etkilemiş. Gerçek dünya bilgileriyle beslenmiş bir YZ modeli kullanılarak; çevresel faktörlerin etkisinin COVID-19 vaka sayılarını ne yönde etkileyeceği önceden tahmin edilebilmiştir (Pirouz & Shaffiee Haghshenas, 2020). ...
... Regresyon modelinde ortalama günlük nem oranı %77,9 vaka sayılarını olumlu etkilerken, günlük hava sıcaklığının maximum 15,4 ° C'ye düşmesi vaka sayılarını olumsuz etkilemiş. Gerçek dünya bilgileriyle beslenmiş bir YZ modeli kullanılarak; çevresel faktörlerin etkisinin COVID-19 vaka sayılarını ne yönde etkileyeceği önceden tahmin edilebilmiştir (Pirouz & Shaffiee Haghshenas, 2020). ...
... It will diminish their moral distress to maintain the social balance. Transparent, true, mindful, and supporting communication with minimum red-tapism at the government level is suggested [72][73][74][75]. AI's roles in measuring the impacts of COVID-19 on environments [76][77][78][79][80], society, education system, health care units, economics, etc., seem to be very important [72][73][74][75]. ...
... Transparent, true, mindful, and supporting communication with minimum red-tapism at the government level is suggested [72][73][74][75]. AI's roles in measuring the impacts of COVID-19 on environments [76][77][78][79][80], society, education system, health care units, economics, etc., seem to be very important [72][73][74][75]. ...
... It will diminish their moral distress to maintain the social balance. Transparent, true, mindful, and supporting communication with minimum red-tapism at the government level is suggested [72][73][74][75]. AI's roles in measuring the impacts of COVID-19 on environments [76][77][78][79][80], society, education system, health care units, economics, etc., seem to be very important [72][73][74][75]. ...
... Transparent, true, mindful, and supporting communication with minimum red-tapism at the government level is suggested [72][73][74][75]. AI's roles in measuring the impacts of COVID-19 on environments [76][77][78][79][80], society, education system, health care units, economics, etc., seem to be very important [72][73][74][75]. ...
The world is now distressed with the coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccination is not done in full fledge and a particular drug is not available to treat COVID-19, modern technologies help humanity fight against it. Data science is a part of modern technological approaches which involve many technologies
like artificial intelligence (AI) and machine learning under a single roof. This chapter focuses on using AI in the management of COVID-19 pandemic for various purposes and making the dichotomy between intelligent man and intelligent machine. AI can function as a radar, robot, computer, machine for medical uses, engine driving, teaching in educational institutions, and other purposes at micro-business and macro-business levels during the current pandemic. AI also brings hope for the prevention of this deadly infection using drones and robots for the disinfection of public places and the cities under
lockdown, for quickly transfer of samples for testing, to deliver medical supplies, food, and small medical devices to a health care provider, and for cleaning and testing in quarantine centers. AI has already arrived in every sector, but few doubts exist asking us: can AI act like a sagacious person? Until now, ‘do not,’ but it is believable that it can be possible soon.
... Regresyon modelinde ortalama günlük nem oranı %77,9 vaka sayılarını olumlu etkilerken, günlük hava sıcaklığının maximum 15,4 ° C'ye düşmesi vaka sayılarını olumsuz etkilemiş. Gerçek dünya bilgileriyle beslenmiş bir YZ modeli kullanılarak; çevresel faktörlerin etkisinin COVID-19 vaka sayılarını ne yönde etkileyeceği önceden tahmin edilebilmiştir (Pirouz & Shaffiee Haghshenas, 2020). ...
... Abstract gives a summary of the research paper with an in-depth analysis of a specified subject. It is often referred to by the readers to ascertain the purpose of the paper quickly [15]. ...
Purpose: The purpose is to map the research work stating the readiness or responsiveness of the higher education institutions towards pandemics and identify the patterns of academic research. Design/Methodology/Approach: Bibliometric analysis is done to map and evaluate the outcomes in the form of the documents published, stating the development of research and understanding the patterns of publication. Findings: Uncommon examinations are attempted to give a multi-faceted technique required to sustain the crisis and build a robust education system in the long run. Likewise, embraced shared research should be empowered and upheld at various levels. Practical implications: The brief interferences provided will enable the readers to get quick and valuable insights into the nature and attributes of academic publishing. Thus, benefiting the researchers in developing their future research agenda and come up with some more innovative ideas. Originality/value: Rare studies using bibliometric analysis are directed to identify the higher education institutions’ responses to the pandemic or efforts required for supporting the” New Normal” in post-pandemic, which is a candid and resourceful exercise to contribute to the existing pool of literature.
... The veracity of the assumed date of onset is questionable and detection window time is uncertain. [31] suggested a binary classification and regression analysis methodology for investigating the COVID-19 outbreak for the sustainable development process. The classification model produces accurate results with respect to confirmed cases. ...
The outbreak of the novel Coronavirus in late 2019 brought severe devastation to the world. The pandemic spread across the globe, infecting more than ten million people and disrupting several businesses. Although social distancing and the use of protective masks were suggested all over the world, the cases seem to rise, which led to worldwide lockdown in different phases. The rampant escalation in the number of cases, the global effects, and the lockdown may have a severe effect on the psychology of people. The emergency protocols implemented by the authorities also lead to increased use in the number of multimedia devices. Excessive use of such devices may also contribute to psychological disorders. Hence, hence it is necessary to analyze the state of mind of people during the lockdown. In this paper, we perform a sentiment analysis of Twitter data during the pandemic lockdown, i.e., two weeks and four weeks after the lockdown was imposed. Investigating the sentiments of people in the form of positive, negative, and neutral tweets would assist us in determining how people are dealing with the pandemic and its effects on a psychological level. Our study shows that the lockdown witnessed more number positive tweets globally on multiple datasets. This is indicative of the positivity and optimism based on the sentiments and psychology of Twitter users worldwide. The study will be effective in determining people's mental well-being and will also be useful in devising appropriate lockdown strategies and crisis management in the future.
... 74 While the final outcome is yet to be confirmed, what is evident is that the pandemic had dual effects: it triggered a health crisis but also unleashed socio-economic issues that severely set back the global sustainable development agenda on poverty eradication. 75 In the face of unilateral behaviour by states as a response measure to COVID-19, the African Development Bank warned of dire consequences. Wilkinson agrees that the COVID-19 pandemic posed a major setback to regional integration in Africa and the continent risked reversing the regional integration gains achieved over the years. ...
The outbreak of the COVID-19 pandemic presented unprecedented challenges to regional bodies across the world. It resulted in a synchronised disruption of the world economy and regional integration agendas, and the re-emergence of nationalism and protectionism. The response to this health emergency differed across regions as regional and local impact of the disease varied. There were coordinated responses to the health crisis by some regional bodies while others saw more local and nationalistic reactions. The argument of this article is that the unilateral closure of borders and the imposition of travel restrictions showed protectionist inclinations and an unwillingness to cede authority to regional bodies. Inspired by the projected implications of the COVID-19 pandemic on the future of regional integration, this article examined the response of both ECOWAS and SADC to the COVID-19 health emergency and considers the implications for the quest for regional integration.
... Pirouz et al. [10] concentrated on the arrangement of confirmed instances of COVID-19 utilizing an Artificial Intelligence (AI) strategy, local area information steering arrangement of the neural network, by adapting a twofold characterization modeling. e proposed model depends on a contextual analysis of China's Hubei territory. ...
The coronavirus disease 2019 (COVID-19) pandemic continues to destroy human life around the world. Almost every country throughout the globe suffered from this pandemic, forcing various governments to apply different restrictions to reduce its impact. In this study, we compare different time-series models with the neural network autoregressive model (NNAR). The study used COVID-19 data in Pakistan from February 26, 2020, to February 18, 2022, as a training and testing data set for modeling. Different models were applied and estimated on the training data set, and these models were assessed on the testing data set. Based on the mean absolute scaled error (MAE) and root mean square error (RMSE) for the training and testing data sets, the NNAR model outperformed the autoregressive integrated moving average (ARIMA) model and other competing models indicating that the NNAR model is the most appropriate for forecasting. Forecasts from the NNAR model showed that the cumulative confirmed COVID-19 cases will be 1,597,180 and cumulative confirmed COVID-19 deaths will be 32,628 on April 18, 2022. We encourage the Pakistan Government to boost its immunization policy.
