A Method about Load Distribution of Rolling Mills Based on RBF Neural Network

Abstract:

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Rolling mills process is too complicated to be described by formulas. RBF neural networks can establish finishing thickness and rolling force models. Traditional models are still useful to the neural network output. Compared with those finishing models which have or do not have traditional models as input, the importance of traditional models in application of neural networks is obvious. For improving the predictive precision, BP and RBF neural networks are established, and the result indicates that the model of load distribution based on RBF neural network is more accurate.

Info:

Periodical:

Edited by:

Fei Hu and Beibei Wang

Pages:

418-422

DOI:

10.4028/www.scientific.net/AMR.279.418

Citation:

D. D. Liu "A Method about Load Distribution of Rolling Mills Based on RBF Neural Network", Advanced Materials Research, Vol. 279, pp. 418-422, 2011

Online since:

July 2011

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$35.00

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