Selection of appropriate defuzzification methods: Application to the assessment of dam performance

•We propose an approach for selecting appropriate defuzzification methods that fulfills the requirements of a group of experts.•We propose a sensitivity analysis of defuzzification methods.•We apply this approach to the assessment of dam performance.•Methods were chosen in relation to the objectives...

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Veröffentlicht in:Expert systems with applications 2017-03, Vol.70, p.160-174
Hauptverfasser: Talon, Aurélie, Curt, Corinne
Format: Artikel
Sprache:eng
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Zusammenfassung:•We propose an approach for selecting appropriate defuzzification methods that fulfills the requirements of a group of experts.•We propose a sensitivity analysis of defuzzification methods.•We apply this approach to the assessment of dam performance.•Methods were chosen in relation to the objectives (decision-support and communication) defined by a group of dam experts.•The approach is applied to a real case. The performance assessment of dams is of major importance for optimizing maintenance management. A methodology is provided here to assess the risk of dam failure using data collected during in-situ inspections and from the design and follow-up files. This assessment takes into account uncertainty associated with the data and the assessment process. The result of this assessment is introduced in a fuzzy frame. This paper presents the approach taken to choose defuzzification methods that allow extracting the information necessary from this possibility distribution so that dam experts can both rank dam maintenance actions and communicate the results of this assessment. This paper first presents the process used to assess dam performance after which it presents the defuzzification methods available. A sensitivity analysis is then performed to select the methods most relevant for our case study. The last part presents the development of a tool useful for the application of defuzzification methods to our problematic and describes a real case study in which the selected defuzzification methods are used.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2016.09.004