Prediction Model of the Cement Strength Based on the Principal Component Wavelet Neural Network

Yong Zheng Zhou; Han Jun Wu; Chun Lai Hu

doi:10.4028/www.scientific.net/AMR.753-755.476

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755Prediction Model of the Cement Strength Based on...

Prediction Model of the Cement Strength Based on the Principal Component Wavelet Neural Network

Abstract:

In this paper, we study the integration of principal component analysis and wavelet neural net work to establish the principle component wavelet neural network model, and apply the model to predict the strength of cement, and using the average prediction error of the strength of cement by the model to compare with the results through the BP neural network model and the principal component neural network model, the average prediction error in this paper is the smallest. Therefore, the method in this paper has guiding significance to control the quality of the cement production.

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Periodical:

Advanced Materials Research (Volumes 753-755)

Pages:

476-480

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.753-755.476

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Online since:

August 2013

Authors:

Yong Zheng Zhou, Han Jun Wu, Chun Lai Hu

Keywords:

Average Prediction Error, Bp Neural Network Model, Principal Component Neural Network Model, Principle Component Wavelet Neural Network Model, Strength of Cement

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References

[1] Hong Yet al, Cao L. Predicting chaotic time series with wavelet networks, physica D. 1995: 85.

Google Scholar

[2] Chen Zhe, Feng Tianjin. Research Developments and Prospects of Wavelet Neural Networks. Journal of Ocean University of Qingdao. 2009. 29(4): 663-666.

Google Scholar

[3] LI Fan. Prediction of final settlements of soft ground in expressway with wavelet neural networks. Journal of Hefei University of Technology. 2001, 24(6): 124-127.

Google Scholar

[4] WAN Jian. A Novel Structure of Wavelet Neural Network and Its Learning Algorithm. Systems Engineering and Electronics. 2002, 24(3): 108-111.

Google Scholar

[5] Zhou Yongzheng, Xiao Biyun, Zhou Yong. The Prediction Research about the Strength of Cement based on Principal Component Neural Network, Communication Software and Networks , 2011 IEEE 3rd International Conference on，Date: 27-29 May 201.

DOI: 10.1109/iccsn.2011.6014431

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