Introducing Interval Analysis in Fuzzy Cognitive Map Framework

摘要

Fuzzy Cognitive Maps (FCMs) is a graphical model for causal knowledge representation. FCMs consist of nodes-concepts and weighted edges that connect the concepts and represent the cause and effect relationships among them. FCMs are used in complex problems involving causal relationships, which often include feedback, and where qualitative rather than quantitative measures of influences are available. They have used for decision support to determine a final state given a qualitative initial knowledge for nodes and weighted edges. A first study on introducing Interval analysis in the FCM framework has been attempted and it is presented in this work. Here a new structure for FCM is proposed with interval weights and a new method for processing interval data input for FCMs is proposed.