Title :
Optimum location on fuzzy clustering method
Author :
Zhang, Ya-jing ; Zhao, Ye ; Zhou, Jing ; Li, Xue-Fei ; Qiao, Jun-jian
Author_Institution :
Coll. of Sci., Agric. Univ. of Hebei, Baoding, China
Abstract :
In this paper, fuzzy cluster method is presented to solve traditional optimum location problem. We consider objects of users as some discrete points. Points are classified by using fuzzy clustering method on condition of large number of them, because the distance between points can be tested by the similarity of axis of the given points. We discuss the single-objective location problem, and construct a model according to realistic situation. The method can also be used in the multi-objective location problem.
Keywords :
computational geometry; fuzzy set theory; pattern classification; pattern clustering; discrete point classification; fuzzy clustering method; multiobjective location problem; optimum location problem; single-objective location problem; Classification algorithms; Clustering methods; Cybernetics; Data mining; Machine learning; Transforms; Transmission line matrix methods; Fuzzy clustering; Fuzzy similar relation; Optimum location;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580496
