DocumentCode
3019716
Title
Evidence fusion methods based on the pretreatment model
Author
Hu, Li-fang ; Guan, Xin ; He, You
Author_Institution
Res. Inst. of Inf. Fusion, Naval Aeronaut. Astronaut. Univ., Yantai, China
fYear
2009
fDate
12-15 July 2009
Firstpage
460
Lastpage
464
Abstract
Dempster´s combination rule is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer theory can involve counter-intuitive results. To solve this problem, this paper combines fuzzy theory to put forward new improved methods of pretreatment mode based on the summary of existing conflict evidences fusion methods. Firstly, the evidence´s conflicting probability is distributed by methods of pretreatment mode which can change high conflict evidences into low conflict evidences. Then, Dempster´s combination rule is used to realize information fusion. Finally, numerical examples and simulation experiments demonstrate the proposed methods can realize the modification ideas and also will provide reasonable results with good convergence efficiency. Although evidences conflict one another highly, good combination results are also obtained.
Keywords
convergence; fuzzy set theory; probability; sensor fusion; uncertainty handling; Dempster´s combination rule; classical Dempster-Shafer theory; conflict evidences fusion methods; convergence efficiency; evidence conflicting probability; evidence fusion methods; fuzzy theory; information fusion; pretreatment model; Convergence of numerical methods; Fuzzy systems; Helium; Information analysis; Numerical simulation; Pattern analysis; Pattern recognition; Stability; Time measurement; Wavelet analysis; Conflict evidence; Dempster´s combination rule; Information fusion; Reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3728-3
Electronic_ISBN
978-1-4244-3729-0
Type
conf
DOI
10.1109/ICWAPR.2009.5207430
Filename
5207430
Link To Document