A new method to determine evidence distance

Chao Shi, Yongmei Cheng, Quan Pan, Yating Lu

科研成果: 书/报告/会议事项章节会议稿件同行评审

6 引用 (Scopus)

摘要

DS evidence theory is a hot topic in multi-sensor data fusion because of its advantages in multi-source information presentation and processing. Considering the difficulties of sensor reliability priority information acquisition, how to compute reliability of sensor via the evidence distance in multisensor data fusion system and how to select consistent evidence for combination via the evidence distance when many homogeneous sensors exist are the open issues. In this paper, a new evidence distance is presented in order to avoid the disadvantage of Diaz's distance measure in the logical selection of tuning parameter and Jousselme's distance measure in not considering the proximity of reference frame to the frame of discernment. This method firstly defines a fuzzy linguistic term set to express the proximity of reference frame to the frame of discernment, in which the semantics of the terms is given by a triangular membership function and a rewarding or penalizing function. Then similarity measurement matrix is achieved by weighting the rewarding or penalizing function using membership degree. Finally Jousselme's distance framework is used to compute the evidence distance. Two numerical examples illustrate the efficiency of the method proposed.

源语言英语
主期刊名2010 International Conference on Computational Intelligence and Software Engineering, CiSE 2010
DOI
出版状态已出版 - 2010
活动2010 International Conference on Computational Intelligence and Software Engineering, CiSE 2010 - Wuhan, 中国
期限: 10 12月 201012 12月 2010

出版系列

姓名2010 International Conference on Computational Intelligence and Software Engineering, CiSE 2010

会议

会议2010 International Conference on Computational Intelligence and Software Engineering, CiSE 2010
国家/地区中国
Wuhan
时期10/12/1012/12/10

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