An Improved Deng Entropy and Its Application in Pattern Recognition

Huizi Cui · Qing Liu · Jianfeng Zhang · Bingyi Kang

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Multi-Criteria Decision Making Rough Sets and Fuzzy Logic Fuzzy and Soft Set Theory

Abstract

How to manage the uncertainty of the basic probability assignment accurately and efficiently is of significance and also an open issue. Plenty of functions have been established to cover the issue, especially Deng entropy recently. Deng entropy can deal with the more complex situation of the focal elements (propositions). However, Deng entropy has some limitations when the propositions are of the intersection. In this paper, a modified function is proposed by considering the scale of the frame of discernment and the influence of the intersection between statements on uncertainty. The proposed belief entropy provides a promising way to measure the uncertain information. Some numerical examples and an application in pattern recognition are used to show the efficiency and accuracy of the proposed belief entropy.

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References

2002On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty 2013Evidential reasoning rule for evidence combination 2018Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy 2016Deng entropy 1983ENTROPY AND SPECIFICITY IN A MATHEMATICAL THEORY OF EVIDENCE 2002Comparison of fuzzy numbers using a fuzzy distance measure 2008Entropy and Specificity in a Mathematical Theory of Evidence 2000Data fusion in the transferable belief model

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