Fuzzy rule-based systems: How to construct a FRBS with MATLAB, R, and Python

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dc.authorscopusidSaliha Karadayı Usta/58220551800
dc.authorwosidSaliha Karadayı Usta/U-8744-2018
dc.contributor.authorKaradayı Usta, Saliha
dc.date.accessioned2025-04-17T14:12:55Z
dc.date.available2025-04-17T14:12:55Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü
dc.description.abstractRule-based reasoning is a widely used technique in artificial intelligence to generate decision supports systems to help practitioners to facilitate quick outputs by simply entering the required inputs. Fuzzy inference systems involve uncertainty, inaccurate information, subjectivity, and ambiguity into knowledge domain to depict the interactions and relationships among the variables. Hence, a fuzzy rule-based systems (FRBS) is paramount of importance in modeling the human thinking. However, although there are numerous papers for FRBS, there is a gap in literature providing advantageous MATLAB, R and Python codes, and applications as a single study. Thus, the purpose of this chapter is to review literature in detail to extract how to conduct FRBSs in MATLAB, R, and Python in detail with examples, and to provide a medical travel company's case study as an illustrative example. The case study's findings highlight how the medical travel company classifies its vendors as either new or current, then considers the market reputation or current patient satisfaction levels of the vendor while keeping the patient's preferences in mind to decide on the collaboration level. In such a case, medical travel companies may be cautious about establishing good relationships or trying to minimize their interactions. In addition, presenting MATLAB, R, and Python roadmaps in a single study provides managerial and practical implications. In determining which platform to use for further research, a practitioner can refer to this manuscript. © 2024 Elsevier Inc. All rights reserved.
dc.identifier.citationKaradayi-Usta, S. (2024). Fuzzy rule-based systems: How to construct a FRBS with MATLAB, R, and Python. In Decision-Making Models (pp. 623-643). Academic Press.
dc.identifier.doi10.1016/B978-0-443-16147-6.00008-6
dc.identifier.endpage643
dc.identifier.isbn978-044316147-6, 978-044316148-3
dc.identifier.scopus2-s2.0-85202887164
dc.identifier.startpage623
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6289
dc.institutionauthorKaradayı Usta, Saliha
dc.institutionauthoridSaliha Karadayı Usta/0000-0002-8348-4033
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofDecision-Making Models: A Perspective of Fuzzy Logic and Machine Learning
dc.relation.publicationcategoryKitap Bölümü - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFuzzy Rule-based Systems (FRBS)
dc.subjectMATLAB
dc.subjectMedical Travel Case Study
dc.subjectPython
dc.subjectRule-based Reasoning
dc.titleFuzzy rule-based systems: How to construct a FRBS with MATLAB, R, and Python
dc.typeBook Chapter

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