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LI Shuangming, GUAN Xin, YI Xiao, SUN Guidong. Combination for Conflicting Interval-Valued Belief Structures with CSUI-DST Method[J]. Chinese Journal of Electronics. doi: 10.1049/cje.2021.00.214
Citation: LI Shuangming, GUAN Xin, YI Xiao, SUN Guidong. Combination for Conflicting Interval-Valued Belief Structures with CSUI-DST Method[J]. Chinese Journal of Electronics. doi: 10.1049/cje.2021.00.214

Combination for Conflicting Interval-Valued Belief Structures with CSUI-DST Method

doi: 10.1049/cje.2021.00.214
Funds:  This work was supported by the Youth Foundation of National Science Foundation of China (62001503), the Excellent Youth Scholar of the National Defense Science and Technology Foundation of China (2017-JCJQ-ZQ-003), and the Special Fund for Taishan Scholar Project (ts201712072)
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  • Author Bio:

    was born in 1986. He is pursing the Ph.D. degree in information and communication engineering from Naval Aviation University. His research interests include intelligent recognition and uncertain information processing. (Email: aminglishuang@126.com)

    (corresponding author) was born in 1978. She is a Ph.D. and Professor in the Naval Aviation University. Her research interests are intelligent information processing and multi-source information fusion. (Email: gxtongwin@163.com)

    (co-corresponding author) was born in 1989. He received the Ph.D. degree from Naval Aviation University. His research interests include complex electromagnetic environment, information fusion and intelligent decision making. (Email: sdwhsgd@163.com)

  • Received Date: 2021-06-19
  • Accepted Date: 2021-11-25
  • Available Online: 2021-12-10
  • Since the basic probability of an interval-valued belief structure (IBS) is assigned as interval number, its combination becomes difficult. Especially, when dealing with highly conflicting IBSs, most of the existing combination methods may cause counter-intuitive results, which can bring extra heavy computational burden due to nonlinear optimization model, and lose the good property of associativity and commutativity in Dempster-Shafer theory (DST). To address these problems, a novel conflicting IBSs combination method named CSUI (conflict, similarity, uncertainty, intuitionistic fuzzy sets)-DST method is proposed by introducing a similarity measurement to measure the degree of conflict among IBSs, and an uncertainty measurement to measure the degree of discord, non-specificity and fuzziness of IBSs. Considering these two measures at the same time, the weight of each IBS is determined according to the modified reliability degree. From the perspective of intuitionistic fuzzy sets, we propose the weighted average IBSs combination rule by the addition and number multiplication operators. The effectiveness and rationality of this combination method are validated with two numerical examples and its application in target recognition.
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