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International Conference on Mechanical Engineering and Technology (ICMET-London 2011)Available to Purchase
Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011
eBook Chapter
168 Sample Selection Method of Neural Network Based on FCM and NN Method Available to Purchase
By
Qinfeng Zhang
Qinfeng Zhang
North China Electric Power Research Institute Co., Ltd
, Beijing
, China
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Page Count:
4
-
Published:2011
Citation
Zhao, Z, Ling, S, & Zhang, Q. "Sample Selection Method of Neural Network Based on FCM and NN Method." International Conference on Mechanical Engineering and Technology (ICMET-London 2011). Ed. Lee, G. ASME Press, 2011.
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In the application of neural network, we often encounter in such problems as the sample set contains too many similar samples or sample features are not representative enough. All these problems may lead to 1Âover learning1Â phenomenon or the case that the results predicted by neural network model deviate largely from the actual results. The paper proposes a method of using Fuzzy C-means (FCM) clustering algorithm and the nearest neighbor (NN) method to establish a neural network sample set. This method can achieve the purpose of establishing the best neural network model with a small and representative sample set, which is a good guide for the application of neural network.
Topics:
Artificial neural networks
Abstract
Keywords
Introduction
The Discussion of Method of the Sample Set Establishment with FCM and NN
The Application of FCM and NN Method in the Sample Set Establishment of Neural Networks
Conclusion
References
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