北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (2): 109-113.doi: 10.13190/j.jbupt.2017-111

• 研究报告 • 上一篇    下一篇

基于证据排序融合的局部冲突信息再分配算法

周莉1, 郭伟震1, 张维华1,2   

  1. 1. 鲁东大学 信息与电气工程学院, 山东 烟台 264025;
    2. 鲁东大学 资产处, 山东 烟台 264025
  • 收稿日期:2017-06-18 出版日期:2018-04-28 发布日期:2018-03-17
  • 作者简介:周莉(1966-),女,教授,硕士生导师,E-mail:zxm2zl@126.com.
  • 基金资助:
    国家自然科学基金重大研究计划项目(91538201);国家自然科学基金青年基金项目(61304052)

Local Conflict Information Redistribution Algorithm Based on Evidence Ranking Fusion

ZHOU Li1, GUO Wei-zhen1, ZHANG Wei-hua1,2   

  1. 1. School of Information and Electrical Engineering, Ludong University, Shandong Yantai 264025, China;
    2. Assets Department, Ludong University, Shandong Yantai 264025, China
  • Received:2017-06-18 Online:2018-04-28 Published:2018-03-17

摘要: 为提高证据冲突度量和融合结果的准确性,提出一种基于证据排序融合的局部冲突信息再分配算法.该算法首先基于证据距离和冲突系数共同度量证据冲突,在此基础上对证据融合顺序进行优化,并对不同证据中不同焦元的冲突度量算法进行改进.进一步,在对证据进行依序融合过程中,将新的证据以及焦元冲突度量结果应用于对局部冲突信息进行再分配.与已有相关算法进行的理论和应用对比分析结果表明,所提算法的证据融合效果更加稳定、可靠.

关键词: 证据组合规则, 目标识别, 冲突度量, 融合

Abstract: In order to improve the accuracy of evidence conflict measure and evidence fusion, a local conflict information redistribution algorithm based on evidence ranking fusion is proposed. The evidence conflict is firstly measured based on the evidence distance and the conflict coefficient in the new algorithm, and on this basis, the order of evidence fusion is optimized and the conflict measure algorithm of different focal elements in different pieces of evidence is improved. Further, during the sequential fusion of evidence, the new conflict measure results of the evidence and the focal element are applied to the redistribution of local conflict information. The performances of the new algorithm and the related algorithms are comparatively analyzed in theory and application, and the results show that the evidence fusion effect of the new algorithm is more stable and reliable.

Key words: evidence combination rule, target recognition, conflict measure, fusion

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