New Evidence Combination Method Based on Redistribution of Global Conflict

Article Preview

Abstract:

The combination of high conflict evidence is a research focus in belief function theory, this paper analyzes two major solving strategy of the modifying rule and the modifying evidence body, and proposes a new evidence synthesis method by modifying rule. In allusion to the combination of high conflict evidence and focusing downwards problem, the method constructs new global conflict measurement under the framework of conjunction combination, which can solve the illogicality of of Shafer conflict measurement. Then the paper designs the solution of local redistribution of global conflict, through choosing the reasonable proportion coefficient, which can overcome focusing downwards and synthesis convergence problem together. Compared with other methods, the new method is more effective to solve the combination problem of high conflict evidence, and meet the quasi-association, and has the higher value of application.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

930-937

Citation:

Online since:

February 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Shafer,G. A Mathematical Theory of Evidence. Princeton University: Princeton, (1976).

Google Scholar

[2] Yager R. On the Dempster-Shafer framework and new combination rule [J]. Information Science, 1987, 41 (2): 93-137.

DOI: 10.1016/0020-0255(87)90007-7

Google Scholar

[3] Smtes P. The combination of evidence in the transferable belief modal[J]. IEEE Trans. On PAMI, 1990, 12 (5): 447-458.

Google Scholar

[4] Dubois D, Prade H, et al. Representation and combination of uncertainty with belief functions and possibility of measures [J]. Computational Intelligence, 1988, 4 (3): 244-264.

DOI: 10.1111/j.1467-8640.1988.tb00279.x

Google Scholar

[5] Daniel M. Associativity in combination of belief functions: a derivation of minC combination[J]. Soft Comput, 2007, 7 (5): 288-296.

DOI: 10.1007/s00500-002-0215-5

Google Scholar

[6] Lefevre E, Colot O, Vannoorenberghe P. Belief functions combination and conflict management [J]. Information Fusion, 2002, 3 (2): 149-161.

DOI: 10.1016/s1566-2535(02)00053-2

Google Scholar

[7] Jia Yuping. Target Recognition Fusion Based on Belief Function Theory [D]. Changsha: Doctoral dissertation of National defense science and technology university, 2009. [in Chinese].

Google Scholar

[8] Murphy K. Combing belief functions when evidence conflicts [J]. Decision Support Systems, 2000, 29 (1): 1-9.

DOI: 10.1016/s0167-9236(99)00084-6

Google Scholar

[9] Deng Y, et al. Combining belief functions based on distance of evidence [J]. Decision Support Systems, 2004, 38 (3): 489-493.

DOI: 10.1016/j.dss.2004.04.015

Google Scholar

[10] Dezert J, Smarandache F. Advances and applications of DSmT for information fusion (Volume 2) [M]. Rehoboth: American Research Press, (2006).

Google Scholar

[11] Sun Quan, Ye Xiuqing, GU Weikang. A new comination rules of evidence theory[J]. Acta Electroniaca Sinica, 2000, 28(8): 117–119. [in Chinese].

Google Scholar

[12] Zhang Jun, Approaches to Conflict Evidence in D-S EvideneeTheory and Its Applications[D]. Nanchang: Master dissertation of Nanchang university, 2007. [in Chinese].

Google Scholar

[13] Wang Yijun, Zhang Hang. A New Synthetic Method of Conflict Evidence[J]. Systems Engineering, 2010, 28 (4): 122-126. [in Chinese].

Google Scholar

[14] Heanni R. Are alternative to Dempster's rule of combination real alternative? Comments on about the belief function combination and the conflict management problem [J]. Information Fusion, 2002, 3 (3): 237-239.

Google Scholar