A Predictive Dynamic Neural Network Model Based on Principal Component Analysis (PCA) and its Application


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We propose a real-time prediction method based on PCA and improved multi-step Elman net. The method not only preserves most original data information, but also eliminates the relativity among data and simplifies the net structure. It can predict the complex and nonlinear systems with dynamic recurrent algorithm. Through training the net has the ability of adapting to the uncertainty of the nonlinear structure, and then reflects the dynamic character of the systems. The hit rate reaches 88.17% to forecast the silicon content in hot metal of a blast furnace with errors ranging from-0.05 percent to 0.05 percent. The results prove that this method is feasible to predict silicon content on blast furnace and also it’s a prediction method of nice future.



Edited by:

Quanjie Gao






Q. Y. Yan and Y. Q. Liu, "A Predictive Dynamic Neural Network Model Based on Principal Component Analysis (PCA) and its Application", Applied Mechanics and Materials, Vol. 127, pp. 19-24, 2012

Online since:

October 2011




[1] R. Chattopadhyay, Anirban Guha and Jayadeva: Journal of Applied Polymer Science, Vol. 91(2004)No. 3, p.1746.

[2] Shinichi Kikuchi, Masakazu Nakanishi: System and Computers in Japan, Vol. 34(2003)No. 6, p.69.

[3] Pham D T, Liu X: International Journal of Systems Science, Vol. 27(1996)No. 2, p.221.

[4] Maria I. Szeliga, Pablo F. Verdes, Pablo M. Granitto and H. Alejandro Ceccatto: International Journal of Neural Systems, Vol. 13(2003)No. 2, p.103.

DOI: 10.1142/s0129065703001492

[5] Tomomichi Nakamura, Devin Kilminster and Kevin Judd: International Journal of Bifurcation and Chaos, Vol. 14(2004)No. 3, p.1129.

[6] Xiaoqun He: The Method of Modern Statistical Analysis and Its Application(The Publishing Company of Renmin University of China, China 1998).

[7] Benjamin W. Wah: International Journal of Computational Intelligence and Applications, Vol. 1(2001)No. 4, p.383.

[8] Yutao Wang, Jianchang Zhou and shi Wang: Iron and Steel, Vol. 34(1999)No. 11, p.7.

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