About this book
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.
Transport agents artificial intelligence artificial neural network case-based reasoning development fuzzy learning management model modeling neural network systems engineering