The Research Of Spatial Data Mining Techniques In Spatial Database

SDM refers to picking up interesting rules from spatial database, such as spatial patterns and characteristics, the universal relations of spatial and non-spatial data and other universal data characteristics implicated in spatial data.Rough set is a new valid mathematical theory developed by Pawlak in recent years, which has the ability to deal with imprecise, uncertain, and vague information. It can find valid, potential and useful knowledge in data. Cloud theory is a new theory handling the system based on the uncertain transition between qualitatives and quantitatives, which can deal with uncertainly problem. It includes cloud model, virtual cloud, cloud operation, cloud transform and uncertainty reasoning.This thesis studies on the theories, techniques and the applications of SDM. The theories of rough set and cloud are introduced into SDM domain. The theories of rough set and cloud in the basal theories and techniques of SDM are studied systematically.Finally, the paper discusses a kind of spatial data mining model based on rough set and cloud model, gives the general method and procedure of this model appreciate for the classification rule mining of GIS. In addition, the paper sets forward a new discretization algorithm of continuous attributes in decision table based on the cloud model to increase the statistical significance and forecast intensity of mining rules. At last, the paper gives a group of GIS data to validate the applicability and validity of this algorithm.