Design And Key Algorithm Research Of Gridding Health Supervision And Management Systems

At present day, digital management pattern has been widely recognized and promotion in succession in domestic small and medium-sized cities, bringing great convenience to the cities, departments and institutions it serves. Therefore how to build a digital management system that both is in consistency with features of a specific industry and has a good compatibility and expansion performance, has become a hot spot of research in computer science and management science.The paper, based on research of related domestic and foreign literature, firstly analyzes the status quo of urban health supervision and management and points out drawbacks of traditional health supervision and management. It also summarizes and absorbs the existing research achievements and by referring to projects cases and using software engineering, grid division theories and technology, a health supervision and management grid division algorithm is proposed. And using this algorithm this paper designs a gridding health supervision and management system in order to transform the traditional, inefficient and extensive management pattern of urban health supervision and management departments; improve the quality of health supervision and management; specify health supervision and management responsibility.Secondly, in order to achieve reasonable division of health supervision and management grid, clustering algorithm is introduced and using the scattered health supervision and management event spots as samples, the clustering algorithm analysis tool is designed and realized. This article designs a two-class grid division mode:the first class specifies initially the supervision and management scope to achieve full coverage of the supervision and management region; and the second class further falls into components grid and events grid. Components grid division further specifies first-class grid according to its division principle while events grid introduces cluster analysis method to divide areas where health events occur frequently. Based on ArcGIS Engine, the paper expands traditional DBSCAN; conducts clustering experiment on first-class grid of No.12of Zhangdian District as an example; realizes the capture of areas of high events occurrence and equal amount distribution; testifies the feasibility of application of clustering algorithm to grid division.Finally, a health supervision and management application system based on grid division is designed, which comprises data acquisition system, regulatory scheduling system, the display system of commanding supervision and comprehensive evaluation system.Research experiments of clustering algorithm suggest that expanded DBSCAB has the function of traditional DBSCAN of removing noise and generating high-density clustering cluster and can re-cluster the clustering cluster selected, facilitating the specifying of its density distribution.And it also is capable of identifying the number of elements of various clusters, thus providing technological support for averaging clustering clusters. The expanded DBSCAN has an important auxiliary and guiding role in practical health inspection and management work in terms of inspecting regions of high event occurrence and equalizing the workload of events inspection.