Combination of Conflict Evidence Based on Bayesian Approximation
Aiqiang Xu · 2016
In order to solve the problems emerged in the situation trying to combine conflict evidences using Dempster-Shafer theory, a new combination rule based on Dubois and Prade rule was raised. A method of using the new rule together with Bayesian Approximation was proposed to combine evidences from different bodies. Firstly the proposition transformation of discernment frame was discussed both in the open and closed world assumption. Secondly the effect of conflict was shown based on the Dempster-Shafer theory and Bayesian theorem. And finally the modified rule depending on the cardinal of set from different evidence bodies was proposed and was showed in the numerical example. Conclusion can be drawn from the example that the new combination rule reserves more information from the combined evidences and Bayesian Approximation reduces the number of focused elements, and using both of them is an effective and accurate method in evidence combination.