A practical review and taxonomy of fuzzy expert systems: methods and applications. Issue 1 (11th September 2019)

• Record Type: Journal Article
• Authors: Tavana, Madjid; Hajipour, Vahid
• Is Part Of: Benchmarking. Volume 27:Issue 1(2020)
• Page Start: 81
• Page End: 136
• Publication Date: 2019-09-11
• Subjects: Fuzzy logic -- Knowledge-based system -- Application domains -- Expert system -- Inference system; Benchmarking (Management) -- Periodicals; Total quality management -- Periodicals; 658.562
• DOI: 10.1108/BIJ-04-2019-0178
• Languages: English
• ISSNs: 1463-5771

Abstract

Abstract : Purpose: Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems. Design/methodology/approach: The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems. Findings: The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field. Originality/value: Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.