会议专题

Automatic Determination of the Initialization Number of Clusters in K-means Clustering Application by Using Co-occurrence Statistics Techniques for Multispectral Satellite Image

Nowadays, clustering is a papular tool for explora tory data analysis, such as K-means and Fuzzy C-mean. Auto matic determination or the initialization number of clusters In k-means clustering application is often needed in advance as an input parameter to the algorithm. In this paper, a method has been developed to determine rhe initialization number of clusters in satellite image clustering application using a data mining algorithm based on the co-occurrence matrix technique. The proposed method was tested using data from unknown number of clusters with multispectral satellite image in Thail and. The results from the tests confirm the effectiveness of the proposed method in rinding the initialization number of clus ters and compared with isodata algorithm.

determination a number of clusters number of cluster K-mean

Kitti Koonsanit Chuleerat Jaruskulchai

Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand

国际会议

2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

成都

英文

1500-1504

2010-12-17(万方平台首次上网日期,不代表论文的发表时间)