The power customers mining based on fuzzy decision tree analysis

Since the seminal work of Zadeh fuzzy set theory (FST) evolved into a valuable extension to traditional techniques, such as regression and decision tree models, for decision analysis conducted under conditions of vagueness and ambiguity. This paper is concerned with the exposition and application of a fuzzy decision tree approaches to a problem involving power customers' data. More specifically, a set of fuzzy 'if... then ...' rules are constructed to classify the level of corporate profit based on a number of characteristics of electric power companies and their experts. The fuzzy rules enable a decision-maker to adjust sale strategy according to different power customers and may give some special policies to higher profit customers. This paper is a new attempt. The result of the research indicates that the fuzzy decision tree technique is very valid in data base of power customers and it will have a good application prospect in this context.