Fuzzy Sets and Triangular Norms: Aggregation in Decision-Aided Intelligent Systems (Intelligent Data-Driven Systems and Artificial Intelligence)

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 environmen