Method Research On Rough Sets-Based Evidence Theory

As a powerful tool in dealing with uncertainty questions, the evidence using in the Evidence theory is given by experts. But the expert's knowledge is limited, subjective and difficult to gam sometimes. With the Rough Sets theory, people can process the undistinguished problem using uncompleted information or knowledge. And also enhance the capability to classify the imprecise data coming from observation or measurement. So the presentation of the Rough Sets theory gives us a new mathematic tool processing the fuzzy information system and uncertainty problem, and is a valuable complement of theory such as Probability theory, Evidence theory, Fuzzy Sets theory etc as well. To the limitation of Evidence theory mentioned above, this paper proposes a new way of knowledge acquirement and also presents a valuable method of the evidence combination and application.Firstly, through further research of the Rough Sets theory, we refine the granule of the classification, and then change the decision attribute of the decision table. Base on these and the relationship between Rough Sets theory and Evidence theory, we compute the evidence's basic belief assignment through classification, and thus we realize the acquisition of evidence.Secondly, we discuss the current research of the evidence combination. To the limitation that the current methods of the evidence combination can't well solved such as interrelation, conflict and importance, and for the goal of the solving the independence of the evidence, a new solution that using the attribute cluster to partition the decision table is proposed. In this paper we also discuss the current research of attribute reduction and give a new method as well.Thirdly, we present two new conceptions: evidence importance and evidence support. And then propose the evidence combination and decision support under the theory this paper present.Finally, on the basis of the efforts above, the design, architecture and realization of the stock market analysis and forecast system base on Rough Sets-based Evidence theory is proposed. And through the experiment we validate the availability of the theory.