Artificial Intelligence

    

Pcarst: a Method of Weakening Conflict Evidence Based on Principal Component Analysis and Relatively Similar Transformation

Authors: Xuan Zhao, Huizi Cui, Zilong Xiao, Bingyi Kang

How to deal with conflict is a significant issue in Dempster-Shafer evidence theory (DST). In the Dempster combination rule, conflicts will produce counter-intuitive phenomena. Therefore, many effective conflict handling methods have been presented. This paper proposes a new framework for reducing conflict based on principal component analysis and relatively similar transformation (PCARST), which can better reduce the impact of conflict evidence on the results, and has more reasonable results than existing methods. The main characteristic feature of the BPAs is maintained while the conflict evidence is regarded as a noise signal to be weakened. A numerical example is used to illustrate the effectiveness of the proposed method. Results show that a higher belief degree of the correct proposition is obtained comparing previous methods.

Comments: 26 Pages.

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Submission history

[v1] 2021-12-23 04:31:07

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