Research On City Transportation Emergency Disposal Decision Support Model

Along with the accelerated urbanization process and the growing scale of development , safety hazards and risks becomes increasingly serious ,breaking caused by various types of emergency incident and the consequent city traffic problems receive more and attention .Rapiddly decision-making and disposal to various types of sudden emergency , can provide effective protection for peoples's lives and property. At present , in order to maintain social harmony and stability , to establish scientific emergency disposal system is becoming increasingly concerned construction tasks among all levels governments.Firstly , this paper analyzed the evacuation problem caused by sudden emergency , based on analyzing the existing evacuation system , proposed an algorithm for the traffic emergency evacuation based on reverse path , applied the classic shortest path algorithm to traffic evacuation , improved the evacuation algorithm by using the strategy of reverse path . This paper also applied the heuristic search to traffic evacuation area , and designed the heuristic search estimate function which is applicable for traffic emergency , improved the efficiency of the algorithm .Based on the analysis of domestic and international emergency disposal system , propsed and established the overall structure for the model based on case-based reasoning decision support . Rapid decision-making and rapid disposal to the incident is most important for emergency disposal , using the method of case-based reasoning , can help decision makers quickly find similar historical cases or plan of the incident , provide important basis and reference for decision-makers . This paper designed an case-based reasoning decision-making model followed by three related steps : case management , reasoning and decision-making , case studies . In case management , proposed an case representation based on combination of XML and object-oriented , solved the problem of uniform representation heterogeneous emergency cases and the problem of storage . In reasoning decision-making , using the rough set technology for case attribute reduction ,using the similarity measure method based on geometric model , using ID3 algorithm for case retrieval and using rule-based reasoning , to complete case-based reasoning and decision-making . Designed a learning process based on case similarity threshold Case studies can make case-based reasoning emergency disposal system with intelligence and learning ablitity , so as to enhance the ability of rapid response and accurate disposal .