DocumentCode
3007895
Title
Improvement of Fusion Algorithm Based on Evidence Theory
Author
Chen Yi ; Wang Gai-Yun ; Li Bing
Author_Institution
Dept. of Comput. Sci., Inst. of Electron. Ind., Guilin
fYear
2008
fDate
25-26 Sept. 2008
Firstpage
539
Lastpage
542
Abstract
The relationship between basic probability assignment (BPA) and belief function in evidence theory is studied. The idea that belief function is regarded as BPA in data fusion is firstly introduced in this paper. An improved fusion algorithm based on distributed fusion method is put forward using this idea. The improved algorithm is called ´distributed fusion algorithm based on belief function assignment´. Through the experimental simulations to the traditional distributed fusion algorithm and the improved algorithm, the results show that the two algorithms are both valid in property identification.
Keywords
belief networks; pattern recognition; sensor fusion; basic probability assignment; belief function; belief function assignment; distributed fusion algorithm; evidence theory; property identification; Bismuth; Computer science; Electronics industry; Genetics; Instruments; Observability; Sensor phenomena and characterization; Evidence Theory; belief function; fusion; identification frend or foe; probability assignment;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location
Hubei
Print_ISBN
978-0-7695-3334-6
Type
conf
DOI
10.1109/WGEC.2008.101
Filename
4637503
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