TY - GEN
T1 - A novel conflict measurement method based on cosine similarity and Deng entropy in Dempster-Shafer evidence theory
AU - Zhang, Xu
AU - Tang, Yongchuan
AU - Zhou, Deyun
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - As a generalization of probability theory, Dempster-Shafer evidence theory is superior in dealing with uncertain information. However, a counter-intuitive result is often obtained when combining highly conflicting evidence. In this paper, a new method based on similarity and Deng entropy of the evidence is proposed to measure the conflict and a new framework of fusing conflicting evidence is built based the proposed method. When most evidence has the same view, this evidence is given the higher weight. Moreover, the lower the entropy of the evidence, the stronger its ability to provide accurate information, and should be paid more attention. Experiments on real data show that this method can effectively solve the combination problem of conflicting evidence and it has a higher accuracy rate in the classification problem compared with other methods.
AB - As a generalization of probability theory, Dempster-Shafer evidence theory is superior in dealing with uncertain information. However, a counter-intuitive result is often obtained when combining highly conflicting evidence. In this paper, a new method based on similarity and Deng entropy of the evidence is proposed to measure the conflict and a new framework of fusing conflicting evidence is built based the proposed method. When most evidence has the same view, this evidence is given the higher weight. Moreover, the lower the entropy of the evidence, the stronger its ability to provide accurate information, and should be paid more attention. Experiments on real data show that this method can effectively solve the combination problem of conflicting evidence and it has a higher accuracy rate in the classification problem compared with other methods.
KW - Classification
KW - Conflict measurement
KW - Dempster-Shafer evidence theory
KW - Deng entropy
KW - Information fusion
UR - http://www.scopus.com/inward/record.url?scp=85142684888&partnerID=8YFLogxK
U2 - 10.1109/SMC53654.2022.9945121
DO - 10.1109/SMC53654.2022.9945121
M3 - 会议稿件
AN - SCOPUS:85142684888
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 3198
EP - 3203
BT - 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022
Y2 - 9 October 2022 through 12 October 2022
ER -