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
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This method is mainly used in cases of quantification of risks of social systems, the “soft systems”.
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Supported by grant BUT IGA No.: FSI-S-17-4785 Engineering application of artificial intelligence methods.
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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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DOI: https://doi.org/10.1007/978-3-319-97888-8_29
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