Extending Deng Entropy to the Open World in the Evidence Theory

Yongchuan Tang, Deyun Zhou, Felix T.S. Chan

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Dempster-Shafer evidence theory (DST) is widely used in intelligent information processing, especially for information fusion. Recently, measuring the information volume in the framework of DST draws a lot of attention. Many theories and tools have been proposed to model the uncertain degree in DST, including Deng entropy. However, Deng entropy and the other uncertainty measures in DST pay no attention to the uncertainty in the frame of discernment (FOD) in the open world, which is the reason of this paper. To address this issue, Deng entropy is extended to the open world in DST framework. With the extended Deng entropy (EDE) in the open world, the uncertain information represented by FOD and the mass function of the empty set now can be properly modelled while measuring the uncertain degree in DST. EDE can be regarded as a generalization of Deng entropy in the open world and it can be degenerated to Deng entropy in the closed world if the mass value of the empty set is zero. A few numerical examples are presented to verify the applicable and useful of the new measure.

源语言英语
主期刊名2018 21st International Conference on Information Fusion, FUSION 2018
出版商Institute of Electrical and Electronics Engineers Inc.
629-634
页数6
ISBN(印刷版)9780996452762
DOI
出版状态已出版 - 5 9月 2018
活动21st International Conference on Information Fusion, FUSION 2018 - Cambridge, 英国
期限: 10 7月 201813 7月 2018

出版系列

姓名2018 21st International Conference on Information Fusion, FUSION 2018

会议

会议21st International Conference on Information Fusion, FUSION 2018
国家/地区英国
Cambridge
时期10/07/1813/07/18

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