摘要
一般空间模糊聚类算法没有区分各属性之间的不平衡性和讨论分类数何时为最佳,针对这一问题,提出了一种加权空间模糊动态聚类算法。该算法首先利用层次分析法得到各属性的权值;然后将权值与空间模糊动态聚类法相结合;最后利用概率统计中的F-分布来确定最佳分类,以提高空间模糊聚类算法的智能性。将文中算法与基于模糊等价关系的传递闭包方法进行比较,试验表明,该算法聚类准确率要明显高于未加权的模糊聚类算法。
Generally the spatial fuzzy clustering algorithm has not differentiated the imbalance between the various attributes and discussed the best classification number.In response to this problem,this paper uses a spatially weighted fuzzy dynamic clustering algorithm.First,the weight of each attribute is accessed using AHP;and then weight is added to the spatial fuzzy dynamic clustering algorithm;finally,the F-distribution of probability statistics is used to determine the best classification number,in order to improve the algorithm＇s intelligence.This algorithm is compared with the transitive closure algorithm based on fuzzy equivalent relations.Tests show that the clustering algorithm＇s accurate rate is higher than not weighted fuzzy clustering algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第17期146-149,共4页
Computer Engineering and Applications
基金
国家高技术研究发展计划(863) No.2006AA10A309
吉林省科技厅重点项目(No.20060213)~~
关键词
层次分析法
模糊等价关系
加权空间模糊动态聚类
最佳分类
analytic hierarchy process
fuzzy equivalence relations
weighted spatial fuzzy dynamic clustering
the best classification
