DocumentCode
3248075
Title
Analysis on KPI factors to choose lands with fuzzy ISODATA clustering
Author
Li, Chengjie ; Liu, Zhen
Author_Institution
Dept. of Mathematica, Zaozhuang Univ., Zaozhuang, China
fYear
2010
fDate
20-21 Oct. 2010
Firstpage
111
Lastpage
113
Abstract
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.
Keywords
convergence; fuzzy set theory; optimisation; pattern clustering; property market; KPI factors; choosing lands problem; fuzzy ISODATA clustering; optimization problems; rapid convergence; fuzzy ISODATA; fuzzy clustering; membership function; realtors;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling (KAM), 2010 3rd International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-8004-3
Type
conf
DOI
10.1109/KAM.2010.5646311
Filename
5646311
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