The Research On Intelligent Distinction System For Species Of Acaroid Mites Of Acaridida Based On Rough Set Theory

Soft computing includes Artifical Neural Networks,Fuzzy Logic,Evolutionary Algorithms,Rough Set (RS) Theory,etc.As a new soft computing,Rough set can analyze and handle imprecise,inconsistent and incomplete data efficiently. Rough set is a powerful tool for analyzing data and is tolerant for faults.Hence,Rough set can overcome shortages of other soft computing in some aspects. So using the advantages of rough set,the paper does some pilot study on the distinction for species of acaroid mites.The research status of intelligent distinction theory and technique are analyzed comprehensively. Then the rough set theory, the method and technique and its current research are discussed generally and the necessity of the application of rough set theory in acaroid mites distinction field is also stated in this dissertation.The method and technique of acaroid mites distinction knowledge acquisition based on rough set is discussed. This dissertation put forward the model of distinction using decision table. By taking the rough set theory as the basis, the algorithm that based on binary discernibility matrix decision rules reduction to conduct the acaroid mites distinction knowledge acquisition is researched with emphasis. The practical aspect of this knowledge acquisition's method is illustrated by a concrete acaroid mites distinction example.The acaroid mites distinction knowledge is analyzed and represented by production rules. Then the inferential strategy and process of knowledge acquisition are described, and the method of generating comprehensive decision rules is stated also.With the usage of the knowledge acquisition and the actual requirements of acaroid mites distinction, the intelligent distinction system for species of acaroid mites based on rough set theory has been developed, and the practical aspect of this system is illustrated by a concrete acaroid mites distinction example. Finally, conclusion is drawn and the future research focus is pointed out.