关键词: 信息融合, 模糊积分, 不确定性

Abstract: Though data mining technique provides powerful support to highly efficient client classification, the technique can not fulfill the task well alone. Because of the limitation of this classifying method, the classifying uncertainty, which is resulted in the difficulties such as the uncertainty, the incompleteness and the deficiency of transcendent knowledge of the information and the complexity of the research object, exists in the real data. From this point of view, the uncertainty of client classification is decreased by combining the method of fuzzy integral and the technique of data mining and a blur density correcting method is put forward to automatically adapt and dynamically evaluate the blur density by using transcendent static information of the training prototype and dynamic information included in the identified result of various classifiers. The emulational result testifies its validity.

Key words: information fusion, fuzzy integral, uncertainty