Disaster management model based on Modified Fuzzy Cognitive Maps

This paper describes the use of a fuzzy cognitive map (FCM) to model disaster reconstruction, based on data collected from the cities of BAM and Baravat. The extended fuzzy cognitive map augmented with an unsupervised learning algorithm has been used transform the associated data into a graphical model. Further to which, a modular approach based on efficient clustering of correlated variables has been adopted to model the sparse data. Discussion and justification of the results is also presented.