Evidence ullage analysis in D-S theory and development

Ruan Jian Xue Bao/Journal of Software

Volumn 15, Issue 1, 2004, Pages 69-75

  Xu, Ling Yu ^a   Zhang, Bo Feng ^a   Xu, Wei Min ^a   Xu, Huai Yu ^b   Guo, Fei Fan ^c  

^a SHANGHAI UNIVERSITY   (China)

^b University of California   (United States)

^c HARVARD UNIVERSITY   (United States)

Author keywords

Combination rule; Conflict; Dempster Shafer; Evidence theory; Evidence ullage; Information fusion; Unconflict

Indexed keywords

INFORMATION THEORY;

COMBINATION RULE; CONFLICT; DEMPSTER SHAFER THEORY; EVIDENCE THEORY; EVIDENCE ULLAGE; INFORMATION FUSION; UNCONFLICT;

INFORMATION ANALYSIS;

EID: 2542569430     PISSN: 10009825     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. Dempster A. Upper and lower probabilities induced by multivalued mapping. Annals of Mathematical Statistics, 1967, 38(2): 325-339.
2. Shafer G. A Mathematical Theory of Evidence. Princeton: Princeton University Press, 1976.
3. Yager R. Using approximate reasoning to represent default knowledge. Artificial Intelligence, 1987, 31(1): 99-112.
4. Dubois D, Prade H. Default reasoning and possibility theory. Artificial Intelligence, 1988, 35(2): 243-257.
5. He B, Mao SY, Zhang YW. Evidence combination based on evidence classification. In: Shunjun W, ed. Proc. of the 2001 CIE Int'l. Conf. on Radar. Piscataway: IEEE, 2001. 732-736.
6. Joussleme AL, Grenier D, Bosse E. A new distance between two bodies of evidence. Information Fusion, 2001, 2(2): 91-101.
7. Wang Z, Hu WD, Yu WX. A combination rule of conflict evidence based on proportional belief assignment. Acta Electronica Sinica, 2001, 29(z1): 1852-1855 (in Chinese with English abstract).
8. Joshi AV, Sahasrabudhe SC, Shankar K. Sensitivity of combination schemes under conflicting conditions and a new method advances in artificial intelligence. In: Wainer J, Carvalho A, eds. Proc. of the 12th Brazilian Symp. on Artificial Intelligence. Berlin: Spring-Verlag, 1995. 39-48.
9. Su YS, Guan JW, Bell DA. Evidence theory and rough set theory. Journal of Software, 1999, 19(3): 277-283 (in Chinese with English abstract).
10. Lefevre E, Colot O, Vannoorenberghe P. A generic framework for resolving the conflict in the combination of belief structures. In: Sotk A, Rom S, Livie H, eds. Proc. of the 3rd Int'l. Conf. on Information Fusion. Sunnyvale: Int. Soc. Inf. Fusion, 2000. 11-18.
11. Josang A. The consensus operator for combining beliefs. Artificial Intelligence, 2002, 141(1-2): 157-170.
12. Lefevre E, Colot O, Vannoorenberghe P. Belief function combination and conflict management. Information Fusion, 2002, 3(2): 149-162.
13. Yager RR. On the aggregation of prioritized belief structures. IEEE Trans. on Systems, 1996, 26(6): 708-717.
14. Liu DY, Yang K, Tang HY. A convex evidence theory model. Journal of Computer Research and Development, 2000, 37(2): 175-181 (in Chinese with English abstract).
15. Sun Q, Ye XQ, Gu WK. A new combination rules of evidence theory. Acta Electronica Sinica, 2000, 28(8): 117-119 (in Chinese with English abstract).