Improved Behavioral Analysis of Fuzzy Cognitive Map Models

  • Miklós F. HatwagnerEmail author
  • Gyula Vastag
  • Vesa A. Niskanen
  • László T. Kóczy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10842)


Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities.

The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems.

This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach.


Banking Fuzzy Cognitive Maps Model uncertainty Multi-objective optimization Bacterial Evolutionary Algorithm 



This research was supported BY the ÚNKP-17-4 New National Excellence Program of the Ministry of Human Capacities.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Miklós F. Hatwagner
    • 1
    Email author
  • Gyula Vastag
    • 2
  • Vesa A. Niskanen
    • 3
  • László T. Kóczy
    • 4
    • 5
  1. 1.Department of Information TechnologySzéchenyi István UniversityGyőrHungary
  2. 2.Department of Leadership and Organizational CommunicationSzéchenyi István UniversityGyőrHungary
  3. 3.Department of Economics and ManagementUniversity of HelsinkiHelsinkiFinland
  4. 4.Department of Information TechnologySzéchenyi István UniversityGyőrHungary
  5. 5.Department of Telecommunications and Media InformaticsBudapest University of Technology and EconomicsBudapestHungary

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