Fault Diagnosis Based on Reasoning Integration of Rough Sets and Evidence Theory
Cai Chang · Transactions of Csice · 2007
Evidence theory is an effective tool in dealing with uncertainty questions. It relies on the expert knowledge to provide evidences, needing the evidences to be independent, and this makes it difficult in application. To solve the problem, a hybrid system of rough sets and evidence theory is proposed. Firstly, the continuous attributes in decision table are discretized with systemic clustering algorithm. Secondly, simplifications are made based on VPRS conditional entropy. Thus, the basic probability assignment for all evidences can be calculated. Thirdly, Dempster's rule of combination is used, and a decision-making is given. Diagnosis in a diesel engine gives a better result by combining evidence theory with rough sets.