An Autonomous FGCM-based System for Surveillance Assets Coordination

摘要

Fuzzy Grey Cognitive Map (FGCM) is an innovative soft computing technique mixing Fuzzy Cognitive Maps and Grey Systems Theory. FGCMs are supervised learning fuzzy- neural systems typically modeled with signed fuzzy grey weighted digraphs, generally involving feedbacks. It is hard to find an accurate mathematical model to describe this decision-making because it includes a high uncertainty and the factors involved interact each other. FGCMs are able to capture and imitate the nature of human being in describing, representing and developing models. They are good at processing fuzzy and grey information and have adaptive, intelligent features. This paper presents a FGCM-based decision support tool, which synthetically takes the related factors into account, offering objective parameters for selecting the fitter surveillance asset. The proposed method is robust, adaptive and simple.