Synthesis Of Conflict Evidence Based On Evidence Discount Corre Ction And Hierarchical Clustering

With the development of science and technology, all kinds of sensor systemfacing complex application background are springing up. A theoretical tool to solvethe multiple source information fusion is desperately needed. D-S evidence theory isdeveloped widely due to the advantages of the uncertainty in the representation andprocessing.In practical applications, D-S evidence theory is only suitable for low conflictsof evidences. While there are strong conflicts between evidences, D-S synthetic ruleswill result in synthesis paradox. For conflict paradox problems, views are divided intotwo kinds, one kind think that we should revise D-S (Dempster-Shafer) syntheticrules while other kind think that the source evidences should be modified. This paperthinks that D-S synthetic rules with the deepest mathematical properties have noproblems and the source evidences should be modified, the views in which aredivided into two kinds: one kind is evidence discount amendment method while theother kind is the method of modifying the evidence source model. This paper choosesthe former due to the uncertainty in conflict evidences, the main contents are includedas follows:Based on the credibility and the similarity of dynamic adjustment, two methodsof evidence discount correction are proposed. The former measures conflict evidenceby the methods of distance and vector cosine, then calculates the credibility ofevidence as the discount coefficient. The latter judge the uncertainty in size anddirection of evidence through the reference evidence to gain the size similarity αi andthe direction similarity βi of each evidence and reference evidence, and then build asimilarity dynamic adjustment model, the result of which will be the discountcoefficient.We can get many groups of evidence from similarity dynamic adjustmentmodel and find one whose conflict is smallest,using D-S synthetic rules to combine itas final synthesis result.In practical applications,conflict evidence may be just a very small part of thesource of evidences.A agglomerative hierarchical clustering method is proposed based on Jousselme distance in this paper. By Clustering, evidence source is dividedinto several classes, the conflict of evidences within the same class is small, whichcan directly combine by the DS combination rule.The conflict of evidences within thedifferent class is strong,so it need to discout evidence, and then using the DScombination rule synthesis.Clustering method can reduce the number of evidencewhich need topretreat.Experiments show that the synthesis results is accurate andreasonable.