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Proceedings Article

Wavelet OHIF Elman neural network model and its predictive control of processing quality

[+] Author Affiliations
Guixiong Liu

South China Univ. of Technology (China)

Jie Yang

South China Univ. of Technology (China) and Guangdong Univ. of Technology (China)

Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973O (May 26, 2011); doi:10.1117/12.889125
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From Conference Volume 7997

  • Fourth International Seminar on Modern Cutting and Measurement Engineering
  • Jiezhi Xin; Lianqing Zhu; Zhongyu Wang
  • Beijing, China | December 10, 2010

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.

© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Guixiong Liu and Jie Yang
"Wavelet OHIF Elman neural network model and its predictive control of processing quality", Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973O (May 26, 2011); doi:10.1117/12.889125; http://dx.doi.org/10.1117/12.889125


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