Paper Title:
Research on the Prediction Model of Laser Surface Hardening Index on Cylinder Liner Based on RBF
  Abstract

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, 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
$32.00
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