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Re-approaching fuzzy cognitive maps to increase the knowledge of a system

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Abstract

Fuzzy cognitive maps is a system modeling methodology which applies mostly in complex dynamic systems by describing causal relationships that exist between its parameters called concepts. Fuzzy cognitive map theories have been used in many applications but they present several drawbacks and deficiencies. These limitations are addressed and analyzed fuzzy cognitive map theories are readdressed. A new novel approach in modelling fuzzy cognitive maps is proposed to increase the knowledge of the system and overcome some of its limitations. The state space approach is used for the new model to disaggregate the concepts into different categories. The disaggregation of the concepts into state concepts, input concepts and output concepts is mathematically formulated. The proposed method and the new model is used for the calculation of a building’s energy consumption and the management of its load. Simulations are performed as a case study testing the new proposed method. The problem of the high energy consumption of the building sector is studied using the new fuzzy cognitive map model. Discussions of the obtained results along with future research directions are provided.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Patras, Rion, Greece

    Mpelogianni Vassiliki & Groumpos Peter P.

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  1. Mpelogianni Vassiliki
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  2. Groumpos Peter P.
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Correspondence to Mpelogianni Vassiliki.

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Mpelogianni, V., Groumpos, P.P. Re-approaching fuzzy cognitive maps to increase the knowledge of a system. AI & Soc 33, 175–188 (2018). https://doi.org/10.1007/s00146-018-0813-0

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