株式会社極東書店トップ商品一覧Fuzzy Sets and Triangular Norms : Aggregation in Decision-Aided Intelligent Systems.

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Fuzzy Sets and Triangular Norms

Fuzzy Sets and Triangular Norms : Aggregation in Decision-Aided Intelligent Systems.

・ISBN 978-1-032-86767-0 hard GB£ 171.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003529088
著者・編者UEnver, Mehmet / OEzcelik, Goekhan (eds.),
シリーズIntelligent Data-Driven Systems and Artificial Intelligence
出版社(CRC Press, UK)
出版年月2026
ページ数320 pp.
言語ENG
ニュース番号<M25-24974>

解説

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.