Access To Technology Research And Application Of Computational Intelligence And Knowledge In Integrated Decision Support System

With the development of economy, how to make correct and efficient decision under the frequently changing and intensely competing condition is the key to obtain predominance at the market. As a result of information techniques' development and progress at very fast speed, making decision in business more and more rely on Information Systems' design and implementation. Decision Support System (DSS) is an important branch of Information Systems used to support managerial work and decision making. DSS integrates techniques of Compute Science, Operation Research and Management Science and already uses widely at decision making in business, city traffic management, health care and medical diagnosis, environment programming and agriculture management, etc. Recently, Artificial Intelligent, Data Mining and Data Warehouse techniques have made a strong impact on research and resign of DSS; otherwise, Fuzzy Set, Rough Set, Artificial Neural Nets, Genetic Algorism and so forth have been used to solve the decision problem. Due to increasing trend of various subjects' integration and connection, application of multi-techniques in DSS' research and design have been roused widely attention.On the basis of discussing different knowledge definition and cognition, this dissertation brings about innovative definition and classification of knowledge for decision making from practical aspect. And then, through comparing methodology and techniques of Artificial Intelligent, Date Mining, Computational Intelligence, Operation Research, Rough Set, and Fuzzy Set, etc. and analyzing their essences, characters, similarities and differences, and advantages and disadvantages, etc. this dissertation puts forward some innovatively combinative methods of vavious methodology and techniques which have certain meaningful direction and enlightened idea in research and design of DSS.Firstly, on the overview of the trend and development in Computational Intelligence and Knowledge Acquisition, this dissertation brings aboutinnovative knowledge definition and its classification. This definition and classification help to specify range of methods and techniques aboutknowledge when building and designing DSS.Secondly, on the basis of discussing Computational Complexity and NP-complete problem, this dissertation studies some methods to deal with NP-complete problem which include Dynamic Programming, Backtracking and Branch-and-bound Algorithms, Local Improvement and Simulated Annealing Algorithms, Hopfield Neural Nets, Genetic Algorithm and etc. Through analyzing various algori thms to solve the Traveling Salesman Problem, how to choice the suitable algorithms when dealing with NP-complete problem has been put forward.Thirdly, on the ground of discussing some representative techniques of reasoning and classification which involve Data Mining, Machine Learning, Rough Set, Fuzzy Set, Neural Computation and Genetic Algorithm, these techniques' essences, characters, similarities and differences, and advantages and disadvantages ;have been analyzed and innovative structure of DSS has been introduced.Fourthly, receivable maniagement subsystem of Decision Support System has been designed on the bas;is of above research and discussion.Finally, through review:integration of various methodology and techniques, this dissertation has a prospect to Artificial Intellignece in theory frame;...