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Proceedings Paper

Wavelet OHIF Elman neural network model and its predictive control of processing quality
Author(s): Guixiong Liu; Jie Yang
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Paper Abstract

There are some difficulties in build the process quality prediction model based on Elman neural network. The traditional Sigmoid activation function often used in the hidden layer, while it is difficult to establish a quantitative relationship between the network size and resolution scale, therefore, a wavelet OHIF Elman neural network model is proposed in this paper, which full use of the neural network weights of the linear distribution and learning convex objective function, so it can avoid the local optimal nonlinear optimization problems. Simulation results show that the wavelet Elman OHIF Elman network decreased 12.9 percent compared with OHIF Elman network which used the sigmoid activation function in hidden layer.

Paper Details

Date Published: 26 May 2011
PDF: 6 pages
Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973O (26 May 2011); doi: 10.1117/12.889125
Show Author Affiliations
Guixiong Liu, South China Univ. of Technology (China)
Jie Yang, South China Univ. of Technology (China)
Guangdong Univ. of Technology (China)


Published in SPIE Proceedings Vol. 7997:
Fourth International Seminar on Modern Cutting and Measurement Engineering
Jiezhi Xin; Lianqing Zhu; Zhongyu Wang, Editor(s)

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