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Fuzzy Logic Control Application for the Risk Quantification of Projects for Automation

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Recent Advances in Soft Computing (MENDEL 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 837))

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Abstract

This article describes the classical approach to risk quantification. This is followed by recommendations of fuzzy sets for advanced risk quantification in the automation project. Different models for fuzzification and defuzzification are presented and the optimum model variants are found with the help of the MATLAB program system.

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Notes

  1. 1.

    This method is mainly used in cases of quantification of risks of social systems, the “soft systems”.

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Acknowledgments

Supported by grant BUT IGA No.: FSI-S-17-4785 Engineering application of artificial intelligence methods.

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Authors and Affiliations

  1. Brno University of Technology, Technická 2, 616 69, Brno, Czech Republic

    Olga Davidova & Branislav Lacko

Authors
  1. Olga Davidova
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  2. Branislav Lacko
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Corresponding author

Correspondence to Branislav Lacko .

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Editors and Affiliations

  1. Department of Applied Computer Science, Institute of Automation and Computer Science, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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Davidova, O., Lacko, B. (2019). Fuzzy Logic Control Application for the Risk Quantification of Projects for Automation. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_29

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