冲突可衡量多源信息融合技术研究

计算机科学 ›› 2013, Vol. 40 ›› Issue (9): 111-115.

冲突可衡量多源信息融合技术研究

陈超,陈性元,汪永伟,王义功

信息工程大学郑州450004 河南省信息安全重点实验室郑州450004;信息工程大学郑州450004 河南省信息安全重点实验室郑州450004;信息工程大学郑州450004 河南省信息安全重点实验室郑州450004;信息工程大学郑州450004 河南省信息安全重点实验室郑州450004

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家高技术研究发展技术(863计划)(2012AA012704),国家973重点基础发展计划(2011CB311801)资助

Research on Conflict-measurable Multiple Information Fusion Technology

CHEN Chao,CHEN Xing-yuan,WANG Yong-wei and WANG Yi-gong

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 针对传统的基于D-S证据理论的多源信息融合系统中不能衡量冲突程度等问题,提出了冲突可衡量多源信息融合系统。首先提出了一种基于决策表的主客观相结合的获取BPA的方法,其次在得到冲突矩阵和一致矩阵的基础上定义了基于冲突/一致度的冲突衡量标准,然后根据证据的平均冲突度确定其在组合公式中的权重系数,最后在充分利用冲突证据所带来的信息的基础上提出了基于冲突信息的组合规则。仿真实验表明,合成结果不仅符合人类逻辑推理,而且极大地减少了不确定性。

关键词: 多源,D-S证据理论,冲突衡量,组合规则,信息融合,基本概率分配中图法分类号TP393.08文献标识码A

Abstract: As traditional multiple source information fusion system based on D-S evidence theory can not measure conflict and solve other problems,a conflict-measurable multiple source information fusion system was presented．Firstly,we presented a method which takes subjectivity and objectivity into consideration to get BPA based on decision-making table．Secondly,we defined a conflict measure based on conflict value and consistent value followed in the conflict matrix and consistent matrix．Next,we determined the weight value of the evidence in the combination rules based on the avera-ge conflict value of the evidence with others．Finally,we made full use of information produced from conflict evidence,and presented a new combination rules based on conflict information．Simulation experiment shows that the conclusion obtained by the fusion method is not only in accordance with human logical reasoning,but also reduces the uncertainty of the conclusion greatly.

Key words: Multiple source,D-S evidence theory,Conflict measure,Combination rules,Information fusion,BPA

陈超,陈性元,汪永伟,王义功. 冲突可衡量多源信息融合技术研究[J]. 计算机科学, 2013, 40(9): 111-115. https://doi.org/

CHEN Chao,CHEN Xing-yuan,WANG Yong-wei and WANG Yi-gong. Research on Conflict-measurable Multiple Information Fusion Technology[J]. Computer Science, 2013, 40(9): 111-115. https://doi.org/

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