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COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS

  • Book
  • © 2010

Overview

Authors:
  1. Da Ruan

    1. Belgian Nuclear Research Centre (SCK • CEN), Mol & Ghent University, Gent, Belgium

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Part of the book series: Atlantis Computational Intelligence Systems (ATLANTISCIS, volume 2)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Computational Intelligence: Past, Today, and Future

    • Cengiz Kahraman, İhsan Kaya, Didem Çinar
    Pages 1-46

  3. Uncertainty in Dynamically Changing Input Data

    • Tiago C. Pais, Rita A. Ribeiro, Luís F. Simões
    Pages 47-66

  4. Decision Making under Uncertainty by Possibilistic Linear Programming Problems

    • Peijun Guo
    Pages 67-83

  5. Intelligent DecisionMaking in Training Based on Virtual Reality

    • Liliane dos Santos Machado, Ronei Marcos de Moraes
    Pages 85-123

  6. A Many-Valued Temporal Logic and Reasoning Framework for Decision Making

    • Zhirui Lu, Jun Liu, Juan C. Augusto, Hui Wang
    Pages 125-146

  7. A Statistical Approach to Complex Multi-Criteria Decisions

    • Pierre L. Kunsch
    Pages 147-182

  8. A Web Based Assessment Tool via the Evidential Reasoning Approach

    • Dong-Ling Xu
    Pages 183-204

  9. An Intelligent Policy Simulator for Supporting Strategic Nuclear Policy Decision Making

    • Suman Rao
    Pages 205-232

  10. Computing withWords for Hierarchical and Distributed Decision-Making

    • Jerry M. Mendel, Dongrui Wu
    Pages 233-271

  11. Realizing Policies by Projects Using Fuzzy Multiple Criteria Decision Making

    • Cengiz Kahraman, İhsan Kaya
    Pages 273-300

  12. Evolutionary ComputationMethods for Fuzzy Decision Making on Load Dispatch Problems

    • Guoli Zhang, Guangquan Zhang, Ya Gao, Jie Lu
    Pages 301-323

  13. Intelligent Decision-Making for a Smart Home Environment with Multiple Occupants

    • Andres Muñoz, Juan A. Botía, Juan Carlos Augusto
    Pages 325-371

  14. Applying a Choquet Integral Based Decision Making Approach to Evaluate Agile Supply Chain Strategies

    • Gϋlçin Bϋyϋközkan
    Pages 373-386

  15. Back Matter

    Pages 387-388
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Keywords

About this book

In recent years, there has been a growing interest in the need for designing intelligent systems to address complex decision systems. One of the most challenging issues for the intelligent system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. The uncertainties result in a lack of the full and precise knowledge of the decision system, including the determining and selection of evaluation criteria, alternatives, weights, assignment scores, and the final integrated decision result. Computational intelligent techniques (including fuzzy logic, neural networks, and genetic algorithms etc.), which are complimentary to the existing traditional techniques, have shown great potential to solve these demanding, real-world decision problems that exist in uncertain and unpredictable environments. These technologies have formed the foundation for intelligent systems.

Authors and Affiliations

  • Belgian Nuclear Research Centre (SCK • CEN), Mol & Ghent University, Gent, Belgium

    Da Ruan

Bibliographic Information

  • Book Title: COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS

  • Authors: Da Ruan

  • Series Title: Atlantis Computational Intelligence Systems

  • DOI: https://doi.org/10.2991/978-94-91216-29-9

  • Publisher: Atlantis Press Paris

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Atlantis Press and the authors 2010

  • eBook ISBN: 978-94-91216-29-9Published: 01 June 2010

  • Series ISSN: 1875-7650

  • Series E-ISSN: 2215-1710

  • Edition Number: 1

  • Number of Pages: XIV, 388

  • Topics: Artificial Intelligence

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