Evidence combination using OWA-based soft likelihood functions
Evidence combination using OWA-based soft likelihood functions
复制标题
使用基于 OWA 的软似然函数进行证据组合
DOI：
10.1002/int.22166
复制
发表时间：
2019-07-22
影响因子：
7
通讯作者：
Liu, Luning
中科院分区：
文献类型：
--
作者：
Fei, Liguo;Feng, Yuqiang;Liu, Luning
Dempster合成法则以其特有的信息表示形式（即质量函数或基本概率赋值）作为一种有效而严密的多尺度信息合成方法，得到了广泛的重视和应用。然而，它也因其不合理的行为和限制性要求而受到批评和争论，例如在某些情况下违反直觉的结果。为了从不同的角度解决这些问题，本文在Dempster-Shafer证据理论的框架下提出了一种替代的融合规则。提出了一种基于软似然函数（SLF）并考虑有序加权平均聚集算子的证据组合规则CR-SLF。给出了一些说明性的例子，相应的分析表明，CR‐SLF融合多个证据的良好性能。为了进一步扩展CR-SLF，从两个方面考虑多样本证据的可靠性，提出了基于可靠性的两种组合规则，包括基于折扣的规则和基于SLF改进的规则。仿真结果表明，基于可靠性的CR‐SLF融合效果优于不考虑可靠性的规则。
Dempster's combination rule has been widely regarded and applied since it is an effective and rigorous method of synthesizing multisource information with its special information representation (ie, mass function or basic probability assignment). However, it has also been criticized and debated upon regarding some of its unreasonable behaviors and restrictive requirements, such as the counterintuitive results in some cases. To address these issues from different perspectives, in this study, an alternative fusion rule is developed under the framework of Dempster‐Shafer evidence theory. A novel evidence combination rule called CR‐SLF is proposed based on soft likelihood functions (SLF) considering the ordered weighted average aggregation operator. Some illustrative examples are shown, and the corresponding analyses demonstrate the good performance of CR‐SLF to fuse multisource evidence. To extend CR‐SLF further, the reliability of multisource evidence is considered from two aspects, subsequently two reliability‐based combination rules are presented, including the discount‐based rule and the SLF improvement‐based rule. The simulation results show that the reliability‐based CR‐SLF has a better fusion effect than the rule without considering the reliability.