New Framework for FCMs Using Dual Hesitant Fuzzy Sets with an Analysis of Risk Factors in Emergency Event

Abstract

As a kind of soft computing tool with strong knowledge representation and causal reasoning ability, fuzzy cognitive maps (FCMs) is a product of fuzzy logic and neural network. A limitation of the current FCMs method is its inability to model the uncertainty that is introduced into a complex system due to the hesitancy of people. Dual hesitant fuzzy sets (DHFSs), which considers the membership and nonmembership degrees by a set of possible values respectively, is an effective tool to model the hesitancy and epistemic uncertainty. Thus, a novel extension of FCMs model called dual hesitant fuzzy cognitive maps (DHFCMs) is proposed in this paper. Firstly, motivated by the idea of Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method, a new similarity measure based on dual hesitant fuzzy distance measure is put forward, and its properties are also discussed. Then, detailed procedure and algorithm for DHFCMs are specified. Moreover, the application steps of the proposed method are provided. Finally, a case study on the huge explosion at Tianjin Port in China in 2015 is given to illustrate the rationality and effectiveness of the proposed method.

Keywords

• Dual hesitant fuzzy sets
• Fuzzy cognitive maps
• Dual hesitant fuzzy cognitive maps
• Similarity measure
• Emergency decision-making