The Combination Rules,Performance Indexes And Applications Of Evidence Reasoning

Compared with other reasoning theories, evidence reasoning theory makesdecisions according to human's way, and can be explained reasonably by usinginfonnation theory. Certain and uncertain zones can be divided with no priorinformation and randomness, and uncertainty from imprecise sources can be managedintuitively. Evidence reasoning is widely used in dealing with the uncertaininformation. In this dissertation, the combination rules, performance indexes andsome applications are discussed in detail. The main contributions are as follows:1. After analyzing the D-S theory and the DSmT developed recently, two newcombination rules, "weigh distribution" and "absorptive method", are given tosolve the conflict problem. Substantive simulations are given to analyze thedifferent ideas and performances of these two rules.2. A performance index scheme of evidence reasoning rules is put forward, including3 parts and 9 items of evaluation criteria. We put forward Anti-high-conflict,complexity, convenience, polarization and conditional polarization, and theevaluation criteria of identity and focusing are also perfected. The performancesof the 12 combination rules are analyzed with the 9 evaluation criteria.3. An amount of simulations are given to evaluate the 12 rules including D-S, DSmT,Smets, Sunquan, Xiangyang, Absorptive method, Xingqinghua, Murphy,Dengyong, Yager, Dubois and Toshiyuki. Using the 9 criteria, we analyze theperformance of the 12 methods in detail. Some suggestions are given from thesimulation results.4. With the application in the recognition of sequential images, the normal process ofevidence reasoning's application in engineering are studied. And the 3 methods ofconstructing basic belief assignment are compared, the recognition of sequentialimages is given based on BP neural network and exponential function. Therecognition results of different methods are then analyzed...