Paper Title:
Prediction of Hardenability of Gear Steel Using Stepwise Polynomial Regression and Artificial Neural Network
  Abstract

The prediction of the hardenability of gear steel has been carried using stepwise polynomial regression and artificial neural networks (ANN). The software was programmed to quantitatively predict the hardenability of gear steel by its chemical composition using two calculating models respectively. The prediction results using artificial neural networks have more precise than the stepwise polynomial regression model. The predicted values of the ANN coincide well with the actual data. So an important foundation has been laid for prediction and controlling the production of gear steel.

  Info
Periodical
Advanced Materials Research (Volumes 118-120)
Edited by
L.Y. Xie, M.N. James, Y.X. Zhao and W.X. Qian
Pages
332-335
DOI
10.4028/www.scientific.net/AMR.118-120.332
Citation
X. H. Gao, T. Y. Deng, H. R. Wang, C. L. Qiu, K. M. Qi, P. Zhou, "Prediction of Hardenability of Gear Steel Using Stepwise Polynomial Regression and Artificial Neural Network", Advanced Materials Research, Vols. 118-120, pp. 332-335, 2010
Online since
June 2010
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Price
$32.00
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