DocumentCode
423765
Title
Ensemble algorithm of neural networks and its application
Author
Liu, We ; Wang, Yuan ; Zhang, Bo-Feng ; Wu, Geng-feng
Author_Institution
Sch. of Comput. Eng. & Sci., Shanghai Univ., China
Volume
6
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
3464
Abstract
Neural network ensemble is a very hot topic in both neural networks and machine learning communities (A. Sharkey, 1999). A new approach named BAGAEN is proposed, in which adaptive genetic algorithm and bootstrap algorithms are employed to increase the different degrees among individual RBF neural networks in order to enhance the generalization ability of a neural network system. The training set for individual RBF neural network is generated by the algorithm based on bootstrap and the result can be obtained by using majority voting method or simple averaging method. Experimental results show that BAGAEN has preferable performance in generating ensembles with strong generalization ability. Finally, BAGAEN is applied to predict the magnitude of earthquake.
Keywords
genetic algorithms; learning (artificial intelligence); neural net architecture; radial basis function networks; RBF neural networks; adaptive genetic algorithm; bootstrap algorithms; machine learning; neural network ensemble; Application software; Bagging; Boosting; Computer networks; Earthquakes; Genetic algorithms; Machine learning; Machine learning algorithms; Neural networks; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380387
Filename
1380387
Link To Document