An Economic Decision Support System based on Fuzzy Cognitive Maps with Evolutionary Learning Algorithm

Abstract

Fuzzy cognitive map (FCM) is a universal tool for modeling dynamic decision support systems. It can be constructed by the experts or learned based on data. FCM models learned from data are denser than those created by experts. We developed an evolutionary learning approach for fuzzy cognitive maps based on density and system performance indicators. It allows to select only the most significant connections between concepts and receive the structure more similar to the FCMs initialized by experts. This paper is devoted to the application of the developed approach to model an economic decision support system. The learning and testing process was accomplished with the use of historical data.