康兵义博士研究小组在改进软似然证据融合上取得进展

论文题目：A modified soft‐likelihood function based on POWA operator

作       者：Xiangjun Mi, Ye Tian and Bingyi Kang（通讯作者）

期刊名称：International Journal of Intelligent Systems（中科院大类2区，CCF推荐国际期刊C类）

发表时间：2020年2月

论文摘要：

 Information fusion is an important research direction. In this field, there are plenty of ways to combine evidence. Initially, Yager proposed a soft‐likelihood function based on the ordered weighted average (OWA) operator to effectively fuse compatible probabilistic evidence. Recently, Song et al proposed a new soft‐likelihood function based on the power ordered weighted average (POWA) operator. However, through analysis, we find Song et al's method has the following two shortcomings: (a) The weight of POWA cannot comprehensively reflect the relation between probability and OWA operator. (b) The soft‐likelihood function does not reflect the preferences of decision makers. To overcome the above problem, we propose a modified soft‐likelihood function. The effectiveness of the proposed method is demonstrated from the perspective of theoretical analysis and numerical examples.

论文链接：https://onlinelibrary.wiley.com/doi/full/10.1002/int.22228