Abstract
How to manage conflict is still an open issue in Dempster-Shafer (D-S) evidence theory. The conflict coefficient k in D-S evidence theory cannot represent conflict reasonably, especially sometimes two Basic Probability Assignments (BPAs) are identical but k is not zero. Generalized information quality, as a concept of data fusion, can effectively measure the uncertainty of BPA. However, how to use the generalized information quality to manage conflicts is still an open question. Therefore, this paper proposed a new correlation coefficient based on generalized information quality to manage conflict. This method can better reflect the correlation coefficient between BPA. Numerical examples are used to demonstrate the effectiveness of the correlation coefficient based on generalized information quality. In addition, a weighted average combination rule based on the new correlation coefficient is presented. A numerical example in target recognition is illustrated to show its validity in combining conflicting evidence.
Highlights
Dempster-shafer’s evidence theory as an uncertainty reasoning method has been widely used in decision making [1]–[3], evidential reasoning [4]–[7], risk evaluation [8], [9], pattern recognition [10], [11], target recognition [12], [13], fault diagnosis [14], etc., [15]–[17]
THE PROPOSED METHOD In order to measure the degree of relevance between two pieces of evidence, a new correlation coefficient based on generalized information quality is proposed as follows: Definition 9: When the discernment frame is, given two Basic Probability Assignments (BPAs), the correlation coefficient based on generalized information quality is defined as follows: First, a factor D is proposed, which reflects the relationship between the targets, and the formula is as follows: D(A, B)
The classical conflict coefficient k is widely regarded as a variable reflecting the conflict between evidences, but studies show that the classical conflict coefficient k cannot accurately represent the conflict between evidences
Summary
Dempster-shafer’s evidence theory as an uncertainty reasoning method has been widely used in decision making [1]–[3], evidential reasoning [4]–[7], risk evaluation [8], [9], pattern recognition [10], [11], target recognition [12], [13], fault diagnosis [14], etc., [15]–[17]. Li et al.’s proposed a generalized information quality, which can efficiently to measure the uncertainty of BPA. The paper proposed a correlation coefficient based on generalized information quality. This method proposed a new factor D, which can more effectively reflect the relationship between BPA. The combination rules in the evidence theory, the information quality [18] and a generalized information quality are introduced. The correlation coefficient based on generalized information quality proposed in this paper is introduced, and the effectiveness of this method is illustrated by a large number of examples. A weighted average combination rule based on correlation coefficient will be proposed and a numerical example will be used to illustrate it.
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