粗糙集理论在雷达故障诊断专家系统中的应用

Expert System is one of the most active and the widest fields of application research in Artificial Intelligence, and it has successful application in many domains. However，with the development of technology and improvement of demands，some problems have appeared such as knowledge acquisition. So the problem that expert system must solve is that how to acquire knowledge and at the basis of which，a correct conclusion must be drawn. Rough sets theory need not any prior knowledge or information, and can analyze and dispose imprecise、inconsistent、incomplete datum. It discloses potential disciples，pick up useful information and reduce information by finding hidden relation among data. The modern radar equipment become increasingly complex, we need very large amount of information to establish the expert system and the knowledge that we received must be existence of a large redundancy. Therefore, to some extent, this also affected the accuracy、efficiency of the diagnosis expert system. For above, we use rough sets in Radar Fault Detection (RFD) Expert System. In this model， knowledge is filtrated before it is input to the knowledge base and the redundancies are eliminated by using the predigest arithmetic of rough set theory. Thereby the structure and performance of the knowledge base are effectively maintained and perfected according to this method.