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Generalized fuzzy cognitive maps: a new extension of fuzzy cognitive maps

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Abstract

A fuzzy cognitive maps (FCM) is a cognitive map within the relations between the elements. FCM has been widely used in many applications such as experts system and knowledge engineering. However, classical FCM is inherently short of sufficient capability of representing and aggregating uncertain information. In this paper, generalized FCM (GFCM) is proposed based on genetic algorithm and interval numbers. An application frame of GFCM is detailed. At last, a numerical example about socio-economic system is used to illustrate the effectiveness of the proposed methodology.

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Acknowledgments

The work is partially supported by National High Technology Research and Development Program of China (863 Program) (Grant No. 2013AA013801), National Natural Science Foundation of China (Grant Nos. 61174022, 61573290, 61503237), China State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (Grant No.BUAA-VR-14KF-02).

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    Authors and Affiliations

    1. School of Computer and Information Science, Southwest University, Chongqing, 400715, China

      Bingyi Kang, Hongming Mo & Yong Deng

    2. Department of the Tibetan Language, Sichuan University of Nationalities, Kangding, 626001, Sichuan, China

      Hongming Mo

    3. Okanagan School of Engineering, Faculty of Applied Science, University of British Columbia, Kelowna, BC, V1V 1V7, Canada

      Rehan Sadiq

    4. School of Electronics and Information Technology, Shanghai Jiao Tong University, Shanghai, 200240, China

      Yong Deng

    5. School of Engineering, Vanderbilt University, Nashville, TN, 37235, USA

      Yong Deng

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    1. Bingyi Kang
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    2. Hongming Mo
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    3. Rehan Sadiq
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    4. Yong Deng
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    Corresponding author

    Correspondence to Yong Deng.

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    Bingyi Kang and Hongming Mo have contributed equally to this work.

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    Kang, B., Mo, H., Sadiq, R. et al. Generalized fuzzy cognitive maps: a new extension of fuzzy cognitive maps. Int J Syst Assur Eng Manag 7, 156–166 (2016). https://doi.org/10.1007/s13198-016-0444-0

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    • DOI: https://doi.org/10.1007/s13198-016-0444-0

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