At The County Level Of Government Emergency Management Experts Aided Decision System Development And Implementation

Public security has become a major problem in the current government management, governments have taken various measures to handle this problem, our government has also taken various managing and technical means to carry on the management. Expert system aided decision system has been applied in many fields. The county government emergency management is the application background. Expert management system for interactive system of experts in various fields and artificial intelligence are established, it can provide intellectual support for government management and decision-making scheme.This paper introduces the need analysis of the county government emergency management decision support system.It includes:business description, system use case analysis, business process analysis, data flow analysis, system function structure, the performance of the system design goals. The system overall design Includes:design and describe the system function, design of database, process design of key algorithm, system security design, system reliability design, the structure design system, and decision support center program design. The article also introduces the system development platform:Windows XP operating system, JSP development platform, MySQL5.1.36database. The implementation of the key modules of the system including:system login, emergency plan, the administrator function, the domain expert interaction function etc. System test part includes:test program, test purpose, test environment, test methods, test content, test cases and test results. System test results shows that the design and realization of the functions can be achieved the intended purpose.As a typical application of artificial intelligence expert decision support system of government emergency management, this paper introduced the realization of the system of county government in public places crowd density estimation system. Firstly, feature extraction and classification of image acquisition has been done. Feature extraction includes wavelet transform, image segmentation, and gray level co-occurrence matrix computation. The designed BP neural network used to classify the crowd density estimation. According to the classification of the population density, the government can make corresponding treatment plan. Experiments show that, system can rational recognition on the input sample density level after training.