航空材料学报2012，Vol.32Issue(5)：92-96,5.DOI:10.3969/j.issn.1005-5053.2012.5.016
Al-Cu-Mg-Ag合金强度性能的支持向量回归预测
Strength Prediction for Al-Cu-Mg-Ag Alloy Based on Support Vector Regression
摘要
Abstract
To explore the strength properties of Al-Cu-Mg-Ag alloy at different aging temperature and aging time, the support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm was proposed to construct a SVR model based on experimental data. In the modeling process, the aging temperature and aging time were employed as input parameters, the tensile strength and yield strength acted as outputs. By comparison with BP neural network, it was found that the prediction accuracy of the established SVR model was higher than that of BPNN model by applying identical training and test samples. This investigation would provide a theoretical foundation for further study on the effect of aging condition on mechanical property, and the optimal design of the aging process for fabricating Al-Cu-Mg-Ag alloy.关键词
Al-Cu-Mg-Ag合金/强度/支持向量回归/粒子群优化/回归分析Key words
Al-Cu-Mg-Ag alloy/strength property/ support vector regression/ particle swarm optimization/regression analysis分类
矿业与冶金引用本文复制引用
唐江凌,蔡从中,皇思洁,肖婷婷..Al-Cu-Mg-Ag合金强度性能的支持向量回归预测[J].航空材料学报,2012,32(5):92-96,5.基金项目
教育部新世纪优秀人才支持计划资助项目(NCET-07-0903) （NCET-07-0903）
教育部留学回国人员科研启动基金资助项目(教外司留[2008]101-1) （教外司留[2008]101-1）
中央高校基本科研业务费资助项目(CDJXS11101135) （CDJXS11101135）
