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• W3018785000 abstract "Fuzzy Cognitive Maps (FCMs) have been used to quantitatively model the dynamics of complex systems and predict their behaviours. However, they are usually unable to address the issues arising from time lags between causes and effects. Accordingly, Generalised Fuzzy Cognitive Maps (GFCMs) have been introduced to overcome this problem. This article deals with a breed of GFCMs that addresses time lags between cause(s) and effect(s), demonstrated by a case-study that deals with the social, economic and technological consequences of heavy rainfall in Kampala, Uganda. The results show that the inclusion of time lags alters both, the final steady-state values of the social, economic and technological consequences of heavy rainfall and the time taken to stabilise. Thus, the inclusion of time lags increases the reliability of GFCMs as a means to quantitatively model the dynamics of complex systems." @default.
• W3018785000 created "2020-05-01" @default.
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• W3018785000 date "2020-07-01" @default.
• W3018785000 modified "2023-09-26" @default.
• W3018785000 title "Generalised fuzzy cognitive maps: Considering the time dynamics between a cause and an effect" @default.
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• W3018785000 doi "https://doi.org/10.1016/j.asoc.2020.106309" @default.
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