Abstract:

In the decision analysis of information systems, the traditional fuzzy clustering analysis has some shortcomings, which not only can not resolve the relevance interfering problem of the characteristic attributes, but also ignores the difference of importance dimensions among the different characteristic attributes. In order to overcome these defects, an improved algorithm is proposed  based on the analytic hierarchy process, the Mahalanobis 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. The Mahalanobis distance algorithm is introduced to build the similarity matrix, and it can resolve the problem of relevance interference of the variables. The experts group decision method is also introduced to decide the best threshold λ, through this method, the adverse effects of the subjective factors to the conclusion of the analysis have been reduced greatly. The application in the supplier relationship management system shows that the improved fuzzy clustering analysis is greatly satisfied with the needs of the decision analysis in information systems.

Key words: fuzzy clustering analysis;analytic hierarchy process;Mahalanobis distance algorithm;group decision;supplier relationship management