Research On DSS Of City Emergency System Based On CRB

Case-based reasoning (CBR) is a recent and important approach to problem solving and learning for knowledge-based systems in AI. It has got a lot of attention in international AI domain because of its particular reasoning style and its successful application over the last few years. Case-based reasoning means to use previous experience in form of cases to understand and solve new problems. A case-based reasoned remembers former cases similar to the current problem and attempts to modify their solutions to fit for the current casc.DSS (Decision Support System DSS ) is developed on integration part, data part and model part. And then DSS has introduced the knowledge system, thus include the composition of artificial intelligence.Due to important application in DSS, CBR has studied, which include CBR cycle, the principle of case, problem description, stored solution, adaptation and adjustment of the case.Secondly, then research based on city emergency system is developed. Analyzing the research background of the city emergency system and investigating the emergency system production both in at home and on abroad, I develop a new architect system. Then, the paper introduces the systematic network framework and each function module of DSS.Then, the CBR theory has been leading the city emergency system in trial, which mako the case scheme produced automatically. Firstly, the researches on case database are presented and describe the content of the case. Secondly, the computation of similarity mensu(?)e is studied. During research on many distance functions, I adopt two ways to compute the similarity of the case which include Heterogeneous Euclidean Overlap Metric and p(?)oportion way.1.nstly, a test about the two forenamed similarity measure methods is given in this paper The test shows that the similarity measure method based on HEOM is the higher among two similarity measure methods about average accuracy.