A novel approximation of basic probability assignment based on rank-level fusion

详细信息    查看全文

• 作者：Yi Yang ; Deqiang Han ; Chongzhao Han ; Feng Cao
• 关键词：Belief approximation ; Distance of evidence ; Evidence combination ; Information fusion ; Rank-level fusion
• 刊名：Chinese Journal of Aeronautics
• 出版年：2013
• 出版时间：August, 2013
• 年：2013
• 卷：26
• 期：4
• 页码：993-999
• 全文大小：911 K

文摘

Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment (BPA) approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach.