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Fuzzy Cognitive Maps Based Models for Pattern Classification: Advances and Challenges

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Soft Computing Based Optimization and Decision Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 360))

Abstract

Fuzzy Cognitive Maps (FCMs) have proven to be a suitable methodology for the design of knowledge-based systems. By combining both uncertainty depiction and cognitive mapping, this technique represents the knowledge of systems that are characterized by ambiguity and complexity. In short, FCMs can be defined as recurrent neural networks that include elements of fuzzy logic during the knowledge engineering phase. While the literature contains many studies claiming how this Soft Computing technique is able to model complex and dynamical systems, we explore another promising research field: the use of FCMs in solving pattern classification problems. This is motivated by the transparency of the decision model attached to these cognitive, neural networks. In this chapter, we revise some prominent advances in the area of FCM-based classifiers and open challenges to be confronted.

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Acknowledgements

This work was partially supported by the Research Council of Hasselt University. Moreover, Gonzalo Nápoles would like to thank Frank Vanhoenshoven, Hasselt University, for his critical remarks and valuable suggestions.

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Authors and Affiliations

  1. Hasselt Universiteit, Agoralaan gebouw D, Diepenbeek, Belgium

    Gonzalo Nápoles & Koen Vanhoof

  2. University of Miami, 5250 University Dr, Miami, FL, USA

    Maikel Leon Espinosa

  3. Central University of Las Villas, Carretera Camajuaní km 5.5, Santa Clara, Cuba

    Isel Grau & Rafael Bello

Authors
  1. Gonzalo Nápoles
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  2. Maikel Leon Espinosa
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  3. Isel Grau
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  4. Koen Vanhoof
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  5. Rafael Bello
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Corresponding author

Correspondence to Gonzalo Nápoles .

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Editors and Affiliations

  1. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada, Granada, Spain

    David A. Pelta

  2. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada , Granada, Spain

    Carlos Cruz Corona

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Nápoles, G., Leon Espinosa, M., Grau, I., Vanhoof, K., Bello, R. (2018). Fuzzy Cognitive Maps Based Models for Pattern Classification: Advances and Challenges. In: Pelta, D., Cruz Corona, C. (eds) Soft Computing Based Optimization and Decision Models. Studies in Fuzziness and Soft Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-64286-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-64286-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64285-7

  • Online ISBN: 978-3-319-64286-4

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