面向冲突证据的改进DS证据理论算法

An improved DS evidence theory algorithm for conflict evidence

DS证据理论在处理不确定信息上的优势在各个领域得到广泛应用。针对传统DS(Dempster-Shafer)存在的证据冲突问题,提出了一种改进的DS证据理论算法。首先,结合皮尔逊相关系数的相关性限制和融合过程零因子的修正,较大程度上减少分配与整体非相关证据体的权值,修正证据体的整体重要程度;然后,按照修正后的基本概率分布(BPA)进行DS组合规则计算,得到融合结果。在解决常见冲突证据和证据体融合数量等方面与其他改进DS证据理论算法进行比较,所提算法收敛速度更快,融合的可信命题基本概率结果更高,因而验证了算法的有效性。

The advantages of DS(Dempster-Shafer) evidence theory in dealing with uncertain information have been widely used in various fields. This paper proposes an improved DS evidence theory algorithm for the existence of evidence conflicts in traditional DS. Firstly,combined with the correlation limitation of Pearson correlation coefficient and the correction of zero factor of fusion process, the weight of distribution and the overall unrelated evidence body is greatly reduced, and the overall importance of the evidence body is corrected. Secondly, the DS combination rule calculation is performed to corrected basic probability assignment(BPA) to obtain the fusion result. Compared with the performance of other improved DS theory algorithms in solving common conflict evidence and the number of evidence body fusion, the proposed algorithm has faster convergence rate and higher fusion BPA on credible proposition, which proves the effectiveness of the proposed algorithm.