Prediction of Hardenability of Gear Steel Using Stepwise Polynomial Regression and Artificial Neural Network

التفاصيل البيبلوغرافية
العنوان: Prediction of Hardenability of Gear Steel Using Stepwise Polynomial Regression and Artificial Neural Network
المؤلفون: Gao, Xiu Hua, Deng, Tian Yong, Wang, Hao Ran, Qiu, Chun Lin, Qi, Ke Min, Zhou, Ping
المصدر: Advanced Materials Research; June 2010, Vol. 118 Issue: 1 p332-335, 4p
مستخلص: 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.
قاعدة البيانات: Supplemental Index
الوصف
تدمد:10226680
DOI:10.4028/www.scientific.net/AMR.118-120.332