Spatial Clustering Algorithm Is Applied Research, Decision Support System In The Housing Security

With the network technology and computer software and hardware technology,the rapid development of database applications,the size,scope has widened.Spatial data and knowledge has been found in the natural process of transformation has become increasingly important role in the development of spatial data mining has become the international hot spots.The purpose of spatial data mining from a large number of complex spatial data mining focused on the potential and useful knowledge for decision support services.Cluster Analysis in the field of data mining has been widely used,the clustering of spatial data is an important research direction.The purpose of this paper is the study of spatial clustering algorithm based on spatial clustering algorithm will be applied to the housing support decision support systems,and housing security for the characteristics of decision support system for improved DBSCAN algorithm to improve the clustering algorithm efficiency,but also to ensure the correctness of algorithms.In this paper,the following tasks:First of all,on the basis of a decision support system theory,introduced a variety of spatial data mining methods as well as various types of excavation and description of the characteristics of knowledge,and commonly used spatial clustering algorithm analysis and comparison.Secondly,housing support for the characteristics of decision support system to the traditional DBSCAN algorithm has been improved:clustering in space before the data pre-processing,in view of the spatial distribution of housing for the region,in the clustering process to reduce the space search time.Finally,a number of experimental design and implementation,verification of the improved DBSCAN algorithm to make sure that the results in the premise of the right,to a certain extent to improve the efficiency of the cluster,and can provide decision support to decision makers.