Comparison of the Defuzzification Methods in Risk Assessment Applications

In risk assessment models the soft computing methods are very popular, because they can handle the uncertainty and imprecision in the data and in the evaluation process. Nevertheless, in practical applications, especially equipment and engineering plans for the project sizing and design studies are needed to precise numerical values. In this paper a fuzzy-based risk assessment model is introduced, where the fuzzy information, which is obtained as the result of the inference, should be defuzzifed in order to give the necessary answer. The main aim of this paper is about presenting the risk assessment calculation and achievement of well-known traditional defuzzification methods using MATLAB Fuzzy Logic Toolbox application.

[1]  László Pokorádi,et al.  The Summarized Weighted Mean of Maxima Defuzzification and Its Application at the End of the Risk Assessment Process , 2014 .

[2]  R. Sadiq,et al.  Water Quality Failures in Distribution Networks—Risk Analysis Using Fuzzy Logic and Evidential Reasoning , 2007, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  P. Rotterová,et al.  New Approach to Fuzzy Decision Matrices , 2017, Acta Polytechnica Hungarica.

[4]  Jeffrey Brown,et al.  Safety Management Systems for Airports. Volume 2: Guidebook , 2009 .

[5]  Vasile Dumbravă,et al.  Using Probability – Impact Matrix in Analysis and Risk Assessment Projects , 2013 .

[6]  Shyi-Ming Chen,et al.  Fuzzy group decision making for evaluating the rate of aggregative risk in software development , 2001, Fuzzy Sets Syst..

[7]  Ouache Rachid,et al.  Safety Instrumented Systems between Reliability and Fuzzy , 2014 .

[8]  Frank Pearson Lees,et al.  Loss prevention in the process industries : hazard identification, assessment, and control , 1980 .

[9]  Monica Sebillo,et al.  Visual Information Systems. Web-Based Visual Information Search and Management, 10th International Conference, VISUAL 2008, Salerno, Italy, September 11-12, 2008. Proceedings , 2008, VISUAL.

[10]  László Pokorádi.  Fuzzy logic-based risk assessment , 2002 .

[11]  J. Mendel.  Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[12]  E. Toth-Laufer,et al.  The effect of aggregation and defuzzification method selection on the risk level calculation , 2012, 2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI).