材料期刊网

Application of Artificial Neural Network to Predicting Hardenability of Gear Steel

GAO Xiuhua , QI Kemin , DENG Tianyong , QIU Chunlin , ZHOU Ping , DU Xianbin

钢铁研究学报(英文版)

The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or the chemical composition by its hardenability. The prediction result is more precise than that obtained from the traditional method based on the simple mathematical regression model.

关键词: artificial neural network (ANN);gear steel;hardenability;20CrMnTiH