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Rapid urbanization has known to have several adverse impacts towards hydrological cycle due to increasing impervious surface and degradation of water quality in stormwater runoff. In the past urban waterways have been confined to narrow river corridors with the channels canalised and concrete and other man-made materials forming the bed and banks o...
Citations
... Multi-objective (Li & Liu, 2016), sequential minimal (Torija et al., 2014), constrained (Fu et al., 2019), layout (T. Huang, 2022), traffic congestion (Jin & Ma, 2018) Management Waste (Béjar et al., 2012;Nowakowski et al., 2018;Pleho & Avdagi , 2015), water (Sidek et al., 2016;Visescu et al., 2017), energy (Januszkiewicz & Paszkowska, 2016), environment (Liu & Gong, 2021;Murillo et al., 2020), data/information (Mukhamediev et al., 2020), crisis (Baharmand & Comes, 2015) Decision-making Decision support system (Calzada et al., 2012), decision making (Elshafei & Negm, 2017), multi-criteria decision support systems (Demetriou et al., 2013), spatial decision support systems (Terribile et al., 2015), environmental decision support systems (Denzer et al., 2013), Electricity consumption forecasting (Zhai et al., 2021), hybrid prediction models (Zhang et al., 2020) ...
Cities are growing, multiplying, increasing in population and complexity (Bettencourt, 2021). Urban planning, in its attempt to manage this ever-increasing complexity, has been integrating artificial intelligence (AI) in its practice for decades. Since urban systems exhibit predictable patterns, AI is attractive to city planners because it enables large data processing capacities in a significantly lower time than it would take human experts to process (Sanchez et al., 2022). But just as cities are growing in complexity, so are AI models, resulting in processes that are concealed from users and decision-makers, making them difficult to comprehend (Linardatos et al., 2020; Mhlanga, 2022). Artificial intelligence is hard to define, because the boundary of what is considered AI is constantly pushed forward as it is incorporated into mainstream use. Within urban planning, Geographic Information Systems (GIS) and the multiple algorithms that enable these programs are such basic tools that they probably would not be considered AI by most of its users. One of the most widely accepted definitions is that AI is “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.”(Haenlein & Kaplan, 2019). By itself, AI is neither ethical nor evil, but this does not mean that AI’s nature is neutral: It is as unbiased as the data we input, as the rules we assign for its operation.
... (4) Hydrology Studies in Hydrology cross scales. At watershed, city, or other macro scales, such literature studies the changes of runoff mechanisms (e.g., processes of formation, evaporation, and infiltration) from the perspectives of Ecological Hydrology [22] , Natural Hydrology [23] , Watershed Hydrology, River Hydrology, Urban Hydrology, and Surface Hydrology, helping identify catchments in urban areas [24] with a particular focus on the balance of urban hydrological processes. At micro scales, studies of various stormwater management and control measures often focus on hydrological performance [25] , functions, and benefits, helping establish natural water cycles through constructed approaches. ...
... Pollutant from the various sources of the catchment will leak and gather with sediment in river beds [22]. Therefore, river water quality degradation problems become even worse. ...
National River Water Plants are located along upper Klang and Gombak river catchment to purify the polluted river using direct contact methods. As the current water quality situation in the study area is poor due to the contribution of anthropogenic activities on the water quality degradation in these urban rivers, the investigation was performed using the Water Quality Index. This paper gives the overall performance of RWTP using Water Quality Index (WQI) calculation methods. The WQI act as the basis of environment assessment towards to river water quality classification under Malaysia National Water Quality Standards. As an overall result, 57 percent from the total effluents achieve target Class II and above and another 43 percent achieve Class III and below regardless of two (2) RWTPs are under target from the average monitoring; RWTP Sg Gisir and RWTP Sg Sentul. However, the result for RWTP Sg Sentul is not yet conclusive since the monitoring duration is less than 2 years. Certainly, RWTP Sg Gisir needs to be taken into consideration for more frequent maintenance of the RWTP or upgrading of the RWTP oxidation tank as suggested in several MBBR/IFAS operation. As to improve the RWTP performance to score higher WQI, the introduction of recycling sludge in the biological tank so it will be a shorter reaction time. Additionally, the RWTP owner should implement a frequent maintenance work into RWTP component especially clarifier, sludge collector, biological oxidation tank and rubbish trap collector.
