Measurement of evidence conflict based on correlation coefficient

Tongxin Xuebao/Journal on Communications

Volumn 35, Issue 5, 2014, Pages 95-100

  Song, Ya Fei ^a   Wang, Xiao Dan ^a   Lei, Lei ^a   Xue, Ai Jun ^a  

^a AIR FORCE ENGINEERING UNIVERSITY   (China)

Author keywords

Conflict measurement; Correlation coefficient; Dempster Shafer evidence theory; Evidence combination; Evidence conflict

Indexed keywords

COMMUNICATION;

CORRELATION COEFFICIENT; DEMPSTER SHAFER EVIDENCE THEORY; EVIDENCE COMBINATION; EVIDENCE CONFLICT;

TECHNOLOGY;

EID: 84902824623     PISSN: 1000436X     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1000-436x.2014.05.013     Document Type: Article

References (21)

1. DEMPSTER A P. Upper and lower probabilities induced by a multi valued mapping[J]. Annual Mathematics and Statistics, 1967, 38(2): 325-339.
2. SHAFER G. A Mathematical Theory of Evidence[M]. Princeton: Princeton University Press, 1976.
3. ZADEH L. Review of a mathematical theory of evidence[J]. AI Magazine, 1984, 5(3): 81-83.
4. ZADEH L. A simple view of the dempster-shafer theory of evidence and its implication for the rule of combination[J]. AI Magazine, 1986, 7(2): 85-90.
5. GUO H W, SHI W K, DENG Y, et al. Evidential conflict and its 3D strategy: discard, discover and disassemble?[J]. Systems Engineering and Electronics, 2007, 29(6): 890-898.
6. LEFEVRE E, COLOT O, VANNOORENBERGHE P. Belief function combination and conflict management[J]. Information Fusion, 2002, (3): 149-162.
7. YAGER R R. On the Dempster-Shafer framework and new combination rules[J]. Information Science, 1987, 41(2): 93-137.
8. DENG Y, SHI W K. A modified combination rule of evidence theory[J]. Journal of Shanghai Jiaotong University, 2003, 37(8): 1275-1278.
9. SUN Q, YE X Q, GU W K. A new combination rules of evidence theory[J]. Acta Electronica Sinica, 2000, 28(8): 117-119.
10. DUBOIS D, PRADE H. A set-theoretic view of belief functions: logical operations and approximations by fuzzy sets[J]. International Journal of General Systems, 1986, 12(3): 193-226.
11. GAO S S, NI L Q, YANG K. A new and better rule for combining sharply conflicting evidences[J]. Journal of Northwestern Polytechnical University, 2009, 27(1): 43-46.
12. HAENNI R. Are alternative to Dempster's rule of combination real alternative? Comments on about the belief function combination and the conflict management problem-E Lefevre[J]. Information Fusion, 2002, 3(3): 237-239.
13. MURPHY C K. Combining belief functions when evidence conflicts[J]. Decision Support Systems, 2000, 29(1): 1-9.
14. 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.
15. HU C H, SI X S, ZHOU Z J, et al. An improved D-S algorithm under the new measure criteria of evidence conflict[J]. Acta Electronica Sinica, 2009, 37(1): 1578-1583.
16. XU L J. Improvement of D-S theory in an information fusion system[J]. Systems Engineering and Electronics, 2004, 26(6): 717-720.
17. LIU W R. Analyzing the degree of conflict among belief functions[J]. Artificial Intelligence, 2006, 170(11): 909-924.
18. JIANG W, PENG J Y, DENG Y. New representation method of evidential conflict[J]. Systems Engineer Ring and Electronics, 2010, 32(3): 562-565.
19. DENG Y, WANG D, LI Q, et al. A new method to analyze evidence conflict[J]. Control Theory & Applications, 2011, 28(6): 839-844.
20. JIANG W, WU C C, JIA J, et al. A probabilistic transformation of basic probability assignment (BPA) in D-S evidence theory[J]. Journal of Northwestern Polytechnical University, 2013, 31(2): 295-299.
21. JOUSSELME A L, GRENIER D, BOSSE E. A new distance between two bodies of evidence[J]. Information Fusion, 2001, (2): 91-101.