Research and Simulation of Spatial Data Classification Using Hierarchical Clustering
Li Juan Yu · Jisuanji fangzhen · 2009
Most of the clustering algorithms ignore dealing with the data of the samples,which influence the classification.For the purpose of improving the capability of the clustering algorithms for dealing with the spatial data,the paper analyzes the Agglomerative Nesting(AGNES) which is a clustering algorithm.The preprocessed AGNES based on immunity was proposed to make the number of elements in each classes after clustering accordant to the criterion defined by users.The improved algorithm was used to resolve efficiently the problem that the edge noise data have a strong impact on the whole classification.At last,an application CityCls was implemented to validate the algorithm by using the MapObjects components based on COM in the Visual C++ environment,and some useful conclusions were made.