Self-tuning of fuzzy belief rule bases for engineering system safety analysis

Jun Liu (), Jian-Bo Yang, Da Ruan, Luis Martinez and Jin Wang

Annals of Operations Research, 2008, vol. 163, issue 1, 143-168

Abstract: A framework for modelling the safety of an engineering system using a fuzzy rule-based evidential reasoning (FURBER) approach has been recently proposed, where a fuzzy rule-base designed on the basis of a belief structure (called a belief rule base) forms a basis in the inference mechanism of FURBER. However, it is difficult to accurately determine the parameters of a fuzzy belief rule base (FBRB) entirely subjectively, in particular for complex systems. As such, there is a need to develop a supporting mechanism that can be used to train in a locally optimal way a FBRB initially built using expert knowledge. In this paper, the methods for self-tuning a FBRB for engineering system safety analysis are investigated on the basis of a previous study. The method consists of a number of single and multiple objective nonlinear optimization models. The above framework is applied to model the system safety of a marine engineering system and the case study is used to demonstrate how the methods can be implemented. Copyright Springer Science+Business Media, LLC 2008

Keywords: Safety analysis; Uncertainty; Fuzzy logic; Belief rule-base; Evidential reasoning; Optimization (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10479-008-0327-0

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