现代制造工程Issue(6)：86-88,115,4.
应用遗传算法优化支持向量机的疲劳裂纹扩展预测
Prediction of fatigue crack propagation based on support vector machine optimized by genetic algorithm
龚兰芳 1张昱2
作者信息
- 1. 广东水利电力职业技术学院,广州,510635
- 2. 广东省科学院自动化工程研制中心,广州,510070
- 折叠
摘要
Abstract
Accurately and rapidly forecasting the fatigue crack propagation is of practical significance and remarkable economic benefit. To forecast fatigue crack propagation exactly,Support Vector Machine optimized by Genetic Algorithm (GA-SVM) is proposed. Genetic Algorithm (GA) is used to determine training parameters of support vector machine in this model,which can gain optimized SVM forecasting model. The experimental results indicate that the proposed GA-SVM model can achieve great accuracy in fatigue crack propagation forecasting.关键词
疲劳裂纹扩展/支持向量机/遗传算法/参数优化Key words
fatigue crack propagation /Support Vector Machine ( SVM )/ Genetic Algorithm ( GA ) /parameter optimization分类
矿业与冶金引用本文复制引用
龚兰芳,张昱..应用遗传算法优化支持向量机的疲劳裂纹扩展预测[J].现代制造工程,2011,(6):86-88,115,4.
