Pressure Fluctuation Based on Cascade Correlation Algorithm in Draft Tube

Abstract:

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The cascade-correlation(CC) is presented as a neural network growing technique which allows one to gradually build network architecture without the need to redefine the number of neurons to be used in a feed forward. In view of the actual situation that the corresponding space curved surface which expresses pressure fluctuation in draft tube is too complex to be analyzed, considering the pressure fluctuation in draft tube, the network model is established based on CC algorithm and it is applied to hydropower station. Comparing with BP neural network, the experimental results show the prediction precision of the final model is higher and the prediction values are in better agreement with the real values.

Info:

Periodical:

Advanced Materials Research (Volumes 121-122)

Edited by:

Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo

Pages:

38-42

DOI:

10.4028/www.scientific.net/AMR.121-122.38

Citation:

L. Y. Wang and W. G. Zhao, "Pressure Fluctuation Based on Cascade Correlation Algorithm in Draft Tube", Advanced Materials Research, Vols. 121-122, pp. 38-42, 2010

Online since:

June 2010

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Price:

$35.00

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