DocumentCode :
1754038
Title :
Research on Samples Self-learning of BP Neural Network Based on Clustering
Author :
Hu, Yingsong ; He, Qing ; Li, Dan
Author_Institution :
Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
1
fYear :
2011
fDate :
28-29 March 2011
Firstpage :
213
Lastpage :
216
Abstract :
The generalization ability of neural network is an important aspect affecting its application. Meanwhile, the selection of training samples has a great impact on this ability. In order to improve the completeness of training samples, a method of samples self-learning of BP neural network based on clustering is put forward in this paper. By using the method of clustering, new samples can be collected in network´s practical application. Network will be more suitable for practical situation after retraining. This method is proved to be simple and creditable. Furthermore, concerned experiments show that this method has obvious effect in improving generalization ability of neural network.
Keywords :
backpropagation; generalisation (artificial intelligence); learning (artificial intelligence); neural nets; pattern clustering; BP neural network; clustering; generalization ability; samples self-learning; Accuracy; Artificial neural networks; Clustering algorithms; Computer science; Indexes; Prediction algorithms; Training; clustering; neural network; samples self-learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location :
Shenzhen, Guangdong
Print_ISBN :
978-1-61284-289-9
Type :
conf
DOI :
10.1109/ICICTA.2011.63
Filename :
5750594
Link To Document :
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