Decision-Making Models: A Perspective of Fuzzy Logic and Machine Learning

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dc.authorscopusidTofigh Allahviranloo / 8834494700
dc.authorscopusidWitold Pedrycz / 58861905800
dc.authorscopusidAmir Seyyedabbasi / 57202833910
dc.authorwosidTofigh Allahviranloo / V-4843-2019
dc.authorwosidWitold Pedrycz / HJZ-2779-2023
dc.authorwosidAmir Seyyedabbasi / HJH-7387-2023
dc.contributor.authorAllahviranloo, Tofigh
dc.contributor.authorPedrycz, Witold
dc.contributor.authorSeyyedabbasi, Amir
dc.date.accessioned2025-04-18T10:37:59Z
dc.date.available2025-04-18T10:37:59Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractDecision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems. Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty. © 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
dc.identifier.doi10.1016/C2022-0-02470-3
dc.identifier.endpage661
dc.identifier.isbn978-044316147-6, 978-044316148-3
dc.identifier.scopus2-s2.0-85202798034
dc.identifier.scopusqualityN/A
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7154
dc.identifier.wosWOS:001244815200313
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorAllahviranloo, Tofigh
dc.institutionauthorPedrycz, Witold
dc.institutionauthorSeyyedabbasi, Amir
dc.institutionauthoridTofigh Allahviranloo / 0000-0002-6673-3560
dc.institutionauthoridWitold Pedrycz / 0000-0002-9335-9930
dc.institutionauthoridAmir Seyyedabbasi / 0000-0001-5186-4499
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofDecision-Making Models: A Perspective of Fuzzy Logic and Machine Learning
dc.relation.publicationcategoryKitap - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectControl Engineering Tool
dc.subjectCyber-Physical Metaverse Manufacturing System Components
dc.subjectDigital Twin
dc.subjectMultiple Criteria Decision-Making
dc.titleDecision-Making Models: A Perspective of Fuzzy Logic and Machine Learning
dc.typeBook Chapter

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