DocumentCode
499017
Title
A dynamic fuzzy measure for multiple classifier fusion
Author
Li, Xue-Fei ; Feng, Hui-min ; Chen, Jun-Fen ; Zhang, Ya-jing
Author_Institution
Coll. of Sci., Agric. Univ. of Hebei, Baoding, China
Volume
1
fYear
2009
fDate
12-15 July 2009
Firstpage
504
Lastpage
508
Abstract
It has been shown that the fuzzy integral is an effective tool for the fusion of multiple classifiers. Of primary importance in the development of the system is the choice of the measure which embodies the importance of subsets of classifiers. In this paper we propose a method for a dynamic fuzzy measure which will change following the pattern to be classified (data dependent). This method uses the neural network which has good study ability. Our experiment results show that this method make the classification accurate improve.
Keywords
fuzzy neural nets; pattern classification; sensor fusion; dynamic fuzzy measure; fuzzy integral; multiple classifier fusion; neural network; Computational intelligence; Computer science; Cybernetics; Educational institutions; Electronic mail; Fuzzy neural networks; Machine learning; Mathematics; Neural networks; Pattern recognition; Fusion; Fuzzy integral; Fuzzy measure; Multiple classifier; Neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3702-3
Electronic_ISBN
978-1-4244-3703-0
Type
conf
DOI
10.1109/ICMLC.2009.5212471
Filename
5212471
Link To Document