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Probability Transform Based on the Ordered Weighted Averaging and Entropy Difference
International Journal of Computers Communications & Control ( IF 2.0 ) Pub Date : 2020-06-08 , DOI: 10.15837/ijccc.2020.4.3743
Lipeng Pan , Yong Deng

Dempster-Shafer evidence theory can handle imprecise and unknown information, which has attracted many people. In most cases, the mass function can be translated into the probability, which is useful to expand the applications of the D-S evidence theory. However, how to reasonably transfer the mass function to the probability distribution is still an open issue. Hence, the paper proposed a new probability transform method based on the ordered weighted averaging and entropy difference. The new method calculates weights by ordered weighted averaging, and adds entropy difference as one of the measurement indicators. Then achieved the transformation of the minimum entropy difference by adjusting the parameter r of the weight function. Finally, some numerical examples are given to prove that new method is more reasonable and effective.

中文翻译:

基于有序加权平均和熵差的概率变换

Dempster-Shafer证据理论可以处理不精确和未知的信息,这吸引了许多人。在大多数情况下,质量函数可以转换为概率,这对于扩展DS证据理论的应用很有用。然而,如何合理地将质量函数转换为概率分布仍然是一个悬而未决的问题。因此,本文提出了一种基于有序加权平均和熵差的概率变换新方法。新方法通过有序加权平均计算权重,并将熵差添加为测量指标之一。然后通过调整权重函数的参数r实现最小熵差的变换。最后,通过算例验证了该方法的合理性和有效性。
更新日期:2020-06-08
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