The generalized maximum belief entropy model

被引：2
|
作者：
Li, Siran [1 ]
Cai, Rui [2 ]
机构：
[1] Southwest Univ, Sch Comp & Informat Sci, Chongqing 400715, Peoples R China
[2] Southwest Univ, Business Coll, Chongqing 402460, Peoples R China
来源：
SOFT COMPUTING | 2022年 / 26卷 / 09期
关键词：
Entropy; Uncertainty measure; Tsallis entropy; Renyi entropy; Shannon entropy; Deng entropy; DECISION-MAKING; UNCERTAINTY MEASURE; TSALLIS ENTROPY; DEFINITION; FUSION; RELIABILITY; TIME;
D O I：
10.1007/s00500-022-06896-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In evidence theory, the generalized belief entropy model unifies Renyi entropy, Tsallis entropy, and Deng entropy. In order to further unify the maximum values of Renyi entropy, Tsallis entropy, and Deng entropy, this paper proposes a maximum model of generalized belief entropy by analyzing the generalized belief entropy model. This model shows that the size of the maximum generalized belief entropy is not related to the specific mass value, but is related to the size of each propositional space, and the maximum values of Renyi-Deng entropy and Tsallis-Deng entropy are obtained through this model. In addition, the applicability of the proposed model is obtained through verification tests and sensitivity analysis of the model.
引用
收藏
页码：4187 / 4198
页数：12
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