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Full Description
This book aims to serve as a comprehensive resource that equips readers with the knowledge and practical skills needed to navigate the intricacies of fuzzy set theory, t-norms, and their integration into decision-aided intelligent systems. It provides a comprehensive understanding of aggregation operators and their role in data fusion, risk analysis, and expert opinion aggregation.
New aggregation operators, entropy measures, t-norm, and t-conorm structures are developed across multiple fuzzy set extensions to better model uncertainty and hesitation in decision-making.
A wide range of real-world applications, including, tourism planning, smart cities, urban mobility, water security, smart campus automation, energy facility siting, and firefighting helicopter selection, are addressed using advanced multi-criteria decision making methods.
The chapters collectively emphasize sustainable, data-driven, and uncertainty-aware decision support, contributing solutions in areas such as environmental protection, resource optimization, public services, and technological infrastructure.
Innovative techniques, such as Lambert W-based aggregation operators, Choquet integral-based entropy, confidence-level aggregation, and fuzzy-machine learning hybrid models, improve the representation of interaction, ambiguity, and complexity in multi-criteria decision problems.
The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including mathematics, industrial engineering, supply chain management, operations research, manufacturing engineering, production engineering, and applied mathematics.
Contents
Preface
About the Editors
List of Contributors
Chapter 1: Lambert Aggregation Operators For Intuitionistic Fuzzy Multi-Criteria Decision Making
Chapter 2: A Group Decision Aggregation-Based IVIF-MARCOS and Goal Programming Approach for Intelligent Decision-Making in Tourism Marketing
Chapter 3: Sustainable Urban Logistics Evaluation in Smart Cities: A Multi-Criteria Group Decision-Making Approach Using the Hesitant Fuzzy Linguistic ARAS Method
Chapter 4: Choquet Integral-Based q-rof Entropy And Its Application
to Information Technologies
Chapter 5: Hybrid Approach using Interval Type-2 Fuzzy TOPSIS and Unsupervised Machine Learning for Water Security and Water Source Area Challenges
Chapter 6: A Group Decision Making by Hesitant Fuzzy Set: Determination of Criterion Weights in Biomass Power Plant Investment
Chapter 7: Fuzzy Set Theory Applications in Smart Cities and IoT
Chapter 8: Smart Campus Process Automation: Process Prioritization through Triangular Fuzzy AHP
Chapter 9: Dombi t-norm and t-conorm Based Aggregation Operators in an
Interval-Valued Fermatean Fuzzy Framework with Confidence Levels
Chapter 10: Evaluation of Heavy Forest Fire Helicopters Using q-rung Orthopair Fuzzy Sets Based TOPSIS Decision Making Model
Chapter 11: Some Interval-Valued Intuitionistic Fuzzy Confidence Level-Based
Aggregation Operators Using Frank t-norm and t-conorms
