Fuzzy Cognitive Maps (FCMs) are an efficient modeling method providing flexibility on the simulated system's design. They consist of nodes-concepts and weighted edges that connect the nodes and represent the cause and effect relationships among them. The performance of FCMs is dependent on the initial weight setting and architecture. This shortcoming can be alleviated and the FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This research proposes a successful attempt to combine fuzzy cognitive maps with decision tree generators. A combined Decision Tree-Fuzzy Cognitive Map (DT-FCM) model is proposed when different types of input data are available and the behavior of this model is studied. In this research work, we introduce a new hybrid modeling methodology for decision making tasks and we implement the proposed methodology at a medical problem.
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Article Synopsis
- - Fuzzy cognitive mapping (FCM) is a participatory research tool that helps clarify causal relationships from different knowledge sources, allowing various groups to agree on future actions.
- - Each FCM consists of three components: factors (causes and outcomes), arrows representing relationships, and weights showing the influence of each factor.
- - The FCM analysis involves four key steps: agreeing on shared meanings, calculating perceived influence, simplifying maps for better communication, and identifying action priorities, all while incorporating local perspectives.
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