Cause and effect analysis by fuzzy relational equations and a genetic algorithm

Alexander P. Rotshtein, Morton Posner and Hanna B. Rakytyanska

Reliability Engineering and System Safety, 2006, vol. 91, issue 9, 1095-1101

Abstract: This paper proposes using a genetic algorithm as a tool to solve the fault diagnosis problem. The fault diagnosis problem is based on a cause and effect analysis which is formally described by fuzzy relations. Fuzzy relations are formed on the basis of expert assessments. Application of expert fuzzy relations to restore and identify the causes through the observed effects requires the solution to a system of fuzzy relational equations. In this study this search for a solution amounts to solving a corresponding optimization problem. An optimization algorithm is based on the application of genetic operations of crossover, mutation and selection. The genetic algorithm suggested here represents an application in expert systems of fault diagnosis and quality control.

Keywords: Cause and effect analysis; Fault diagnosis; Fuzzy relational equations; Genetic algorithm (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:9:p:1095-1101

DOI: 10.1016/j.ress.2005.11.041

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