The Dynamic Extensions of Fuzzy Grey Cognitive Maps

Jun Chen; Xudong Gao; Jia Rong; Xiaoguang Gao

doi:10.1109/ACCESS.2021.3096058

IEEE Access (Jan 2021)

The Dynamic Extensions of Fuzzy Grey Cognitive Maps

Jun Chen,
Xudong Gao,
Jia Rong,
Xiaoguang Gao

Affiliations

Jun Chen: ORCiD; School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China
Xudong Gao: ORCiD; School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China
Jia Rong: ORCiD; Department of Data Science and AI, Faculty of IT, Monash University, Clayton, VIC, Australia
Xiaoguang Gao: School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China

DOI: https://doi.org/10.1109/ACCESS.2021.3096058
Journal volume & issue: Vol. 9
pp. 98665 – 98678

Abstract

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Fuzzy Cognitive Map is recognized as an important model in soft computing. The Fuzzy Cognitive Map theory studies often treat uncertainty modeling and dynamic modeling separately. So far, there is no single Fuzzy Cognitive Map that can deal with uncertain data and dynamic environments simultaneously. This paper proposed an environment model to describe the link between changing weights and the dynamic environment. As the extensions of the classic Fuzzy Grey Cognitive Map, two dynamic models were designed and implemented in this work: Dynamic Fuzzy Grey Cognitive Map and Dynamic Fuzzy General Grey Map. In this work, we also analyze the characteristics of the two models and evaluate their performance using industrial control problems. The results showed that the proposed models could well handle uncertain data in dynamic environments.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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