This book, "ANN-Based MAGDM Problems under Intuitionistic Fuzzy Environment," presents a systematic framework for addressing Multi-Attribute Group Decision-Making (MAGDM) problems under uncertainty by integrating intuitionistic fuzzy set (IFS) theory with Artificial Neural Networks (ANN). The book explains how IFS effectively models hesitation and imprecision in expert judgments, while ANN supports learning-based and consistent decision structures. It offers a comprehensive treatment of IFS concepts tailored to MAGDM, including aggregation operators, ranking procedures, and defuzzification strategies.The work further develops ANN architectures suitable for intuitionistic fuzzy inputs and discusses learning rules, convergence behavior, and ranking aspects within uncertain environments. Several illustrative case studies demonstrate real-world applicability across engineering, management, and data-driven decision systems. Designed for researchers, doctoral scholars, and postgraduate students, the book provides both theoretical insight and practical methodology for solving complex group decision-making problems.
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