Analysis on KPI Factors to Choose Lands with Fuzzy ISODATA Clustering
Clustering is an example of a class of optimization problems. In the classical clustering, an item must belong to any one cluster. But fuzzy clustering describes more accurately the ambiguous type of structure in data. The fuzzy ISODATA clustering exhibits the rapid convergence in finding the best classification program when the classification number is given. In this paper, we propose the algorithm to solve the choosing lands problem and show the result of the experiment The result is satisfied to realtors in choosing lands.
fuzzy clustering realtors fuzzy ISODATA membership function
Chengjie Li Zhen Liu
Department of Mathematica Zaozhuang University Shandong Province, China Department of Computer aozhuang University Shandong Province, China
国际会议
2010 Third International Symposium on Knowledge Acquisition and Modeling(第三届知识获取与建模国际研讨会 KAN 2010)
武汉
英文
111-113
2010-10-20（万方平台首次上网日期，不代表论文的发表时间）