World Scientific
  • Search
  •   
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website www.worldscientific.com.

System Upgrade on Tue, Oct 25th, 2022 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.
Computational Intelligence In Complex Decision Systems cover

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.


Contents:
  • Computational Intelligence: Past, Today, and Future (C Kahraman et al.)
  • Uncertainty in Dynamically Changing Input Data (T C Pais et al.)
  • Decision Making under Uncertainties by Possibilistic Linear Programming Problems (P Guo)
  • Intelligent Decision Making in Training Based on Virtual Reality (L dos Santos Machado & R Marcos de Moraes)
  • A Many-Valued Temporal Logic and Reasoning Framework for Decision Making (Z Lu et al.)
  • A Statistical Approach to Complex Multi-Criteria Decisions (P L Kunsch)
  • A Web Based Assessment Tool via the Evidential Reasoning Approach (D-L Xu)
  • An Intelligent Policy Simulator for Supporting Strategic Nuclear Policy Decision-Making (S-M Rao)
  • Computing with Words for Hierarchical and Distributed Decision Making (J M Mendel & D Wu)
  • Realizing Policies by Projects Using Fuzzy Multiple Criteria Decision Making (C Kahraman & İ Kaya)
  • Evolutionary Computation Methods for Fuzzy Decision Making on Load Dispatch Problems (G Zhang et al.)
  • Intelligent Decision-Making for a Smart Home Environment with Multiple Occupants (A Muňoz et al.)
  • Applying a Choquet Integral Based Decision to Evaluate Agile Supply Chain Strategies (G Büyüközkan)

Readership: Academics and professional in the field of complex decision systems.