Synopses & Reviews
Decision making is a multi-faceted and challenging, yet important task. A decision maker normally has to take into consideration a number of alternatives, which often conflict with one another, before reaching a good decision. To cope with the challenges of decision making, decision support systems have been developed to provide assistance in human decision making processes. The key to decision support systems is to collect information/data, analyse the information/data collected, and subsequently make quality and informed decisions. In this aspect, intelligent reasoning and learning techniques have emerged as a powerful approach to solving real-world decision making problems. The main aim of this research handbook is to present a small fraction of techniques stemmed from artificial intelligence, as well as other complementary methodologies, that are useful for developing intelligent decision support systems. In addition, application examples on how the intelligent decision support systems can be deployed to undertake decision making problems in a variety of domains are presented. Among the topics covered in this book include • modelling and design of intelligent decision support systems • artificial neural networks, genetic algorithm, and fuzzy systems for intelligent decision making • case based reasoning and agent-based systems for intelligent decision making • application of intelligent decision support systems to business, management, manufacturing, engineering, biomedicine, transportation and food industries.
Synopsis
The present "Vol 1: Techniques and Applications" of the "Handbook on Decision Making" presents a useful collection of AI techniques , as well as other complementary methodologies, that are useful for the design and development of intelligent decision support systems. Application examples of how these intelligent decision support systems can be utilized to help tackle a variety of real-world problems in different domains, such as business, management, manufacturing, transportation and food industries, and biomedicine, are presented. The handbook includes twenty condensed chapters, which are divided into two parts, i.e., (i) modelling and design techniques for intelligent decision support systems; and (ii) reviews and applications of intelligent decision support systems.
Synopsis
This handbook presents a useful collection of AI techniques, as well as other complementary methodologies, useful for the design and development of intelligent decision support systems. The book includes a variety of real-world problems in different domains.
Table of Contents
Part I Modelling and Design Techniques for Intelligent Decision Support Systems.- Part II Reviews and Applications of Intelligent Decision Support Systems.