Research on the Prediction Model of Laser Surface Hardening Index on Cylinder Liner Based on RBF

Abstract:

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Based on the data obtained from the perpendicular experiment of laser surface hardening on HT150 cylinder liner of a certain motor engine, a Radial Basis Function (RBF) neural network prediction model of laser surface hardening index about HT150 cylinder liner is established by Matlab neural network toolbox in this paper. The parameters of input layer are affirmed by analyzing influential factors of the hardened index ,and the best form of the network is affirmed by selecting suitable spread in function-newrb( ),and as a result, the prediction accuracy and the adaptability of the network are improved. The result of testing the model indicates that the model based on RBF neural network has a good generalizing capability. Compared with traditional Back-Propagation Network (BP network), the result indicates that RBF has better accuracy and adaptability.

Info:

Periodical:

Advanced Materials Research (Volumes 148-149)

Edited by:

Xianghua Liu, Zhengyi Jiang and Jingtao Han

Pages:

215-218

DOI:

10.4028/www.scientific.net/AMR.148-149.215

Citation:

X. L. Wu and F. Ren, "Research on the Prediction Model of Laser Surface Hardening Index on Cylinder Liner Based on RBF", Advanced Materials Research, Vols. 148-149, pp. 215-218, 2011

Online since:

October 2010

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Price:

$35.00

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