Ensemble Interval-Valued Fuzzy Cognitive Maps

As a novel generalization of fuzzy cognitive map (FCM), interval-valued FCM (IVFCM) can provide more flexibility in modeling that increasingly complex system with uncertainty. However, the problem of aggregating IVFCMs has not been considered to this day. Concerning this key point, we propose an ensemble IVFCMs via evidential reasoning (ER) approach. First, we give a detailed analysis of IVIFS in terms of evidence theory and introduce the concept of augmented connection matrix within the framework of IVFCMs. Second, we present a theory of ensemble IVFCMs using the former work and ER approach, particular emphases are put on assessing the weights of different IVFCMs and aggregating them. Both theoretical analysis and practical examples show that the ensemble IVFCMs not only reflects the importance levels of different maps but also can achieve the goal of merging of information from different maps in system modeling.