对模糊聚类分析法的改进和其在SRM中的应用_黄闽英.pdf

CN431258/ T P 2011 33 6 ISSN 1007130X COMPUTER ENGINEERING SCIENCE Vol33, No6, 2011 : 1007130X(2011) SRM Modification of the Fuzzy Clustering Analysis M ethod and Its Application in SRM , HUANG Minying, MU Rui ( , 610041) (School of Computer Science nd Technology, Southwest University for N tion lities, Chengdu 610041, Chin ) : 针对传统模糊聚类分析法在信息系统的决策分析中无法有效解决各因素之间的相关性 扰, 以及不同特征属性对聚类目标存在重要性差异等问题, 本文提出一种融合层次分析法Mahalanobis 距离 法及专家群决策法的改进模糊聚类分析法在特征属性的重要性处理环节, 层次分析法用于判断不同特 征属性的相对重要性差异; 引入Mahalanobis 距离法进行相似矩阵的构建, 能解决变量之间的相关性 扰 问题; 专家群决策法用于确定最佳阈值, 能最大程度地降低主观因素对评价结论的不利影响在SRM 中的应用实验结果表明, 改进的模糊聚类分析法在客观性和准确性上更能满足信息系统决策分析的需要 Abstr ct: In the decision analysis of information systems, the traditional fuzzy clustering analysis has some shortcomings, w hich not only can not resolve the relevance interfering problem of the charac teristic attributes, but also ignores the difference of importance dimensions among the different charac teristic attributes. In order to overcome these defects, an improved algorithm is proposed based on the analytic hierarchy process, the M ahalanobis distance algorithm and the group decision method. In the link of importance treating, an analytic hierarchy process is used to estimate the importance dimensions of different characteristic attributes. T he M ahalanobis distance algorithm is introduced to build the simi larity matrix, and it can resolve the problem of relevance interference of the variables. T he experts group decision method is also introduced to decide the best threshold , through this method, the ad verse effects of the subjective factors to the conclusion of the analysis have been reduced greatly. T he application in the supplier relationship management system show s that the improved fu