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

  • Olga Davidova
  • Branislav Lacko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 837)

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.

Keywords

Project Risk control Risk quantification Fuzzy sets Fuzzy control Defuzzification 

Notes

Acknowledgments

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

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Brno University of TechnologyBrnoCzech Republic

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