(Jiang W, Zhang A, Deng Y. A novel information fusion method based on our evidence conflict representation[J]. J of Northwestern Polytechnical University, 2010, 28(1): 27-32.)
(Xiong Y M, Yang Z P, Qu X F. Novel combination method of conflict evidence based on evidential model modification[J]. Control and Decision, 2011, 26(6): 883-887.)
(Hou J. The combination rules, performance indexes and application of evidence reasoning[D]. Xi’an: Northwestern Polytechnical University, 2006: 38-41.)
(Lu W X, Liang C Y, Ding Y. A method determining the objective weights of experts based on evidence distance[J]. Chinese J of Management Science, 2008, 16(6): 95-98.)
(Peng Y, Shen H R, Ma Y Y. A new fusion method for conflicting evidence[J]. Acta Armamentarii, 2011, 32(1): 79-85.)
[16]
Smets P. The combination of evidence in the transferable belief model[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1990, 12(5): 447-458.
[17]
Yager R R. On the Dempster-shafer framework and new combination rules[J]. Information Science, 1989, 41(2): 93-137.
(Xing Q H, Lei Y J, Liu F X. One combination rule of evidence theory based on distributing conflict in proportion[J]. Control and Decision, 2004, 19(12): 1389-1390.)
[26]
Deng Y, Shi W K, Zhu Z F, et al. Combining belief functions based on distance of evidence[J]. Decision Support Systems, 2004, 38(3): 489-493.
(Quan W, Wang X D, Wang J, et al. A combination rule of evidence theory based on brief max-entropy model[J]. Control and Decision, 2012, 27(6): 899-903.)
[29]
Haenni R. Are alternatives to Dempster’s rule of combination real alternatives? Comments on “about the belief combination and the conflict management problem”[J]. Information Fusion, 2002, 3(3): 237-239.
[30]
Murphy C K. Combination belief function when evidence conflict[J]. Decision Support System, 2000, 29(1): 1-9.
[31]
王肖霞. 冲突证据合成规则的研究[D]. 太原: 中北大学, 2007: 39-46.
[32]
(Wang X X. Research on combination rule of evidence theory[D]. Taiyuan: North University of China, 2007: 39-46.)
[33]
Horiuchi T. Decision rule for pattern classification by integrating interval feature values[J]. Pattern Analysis and Machine Intelligence, 1998, 20(4): 440-448.
