首页> 外文会议>E-Learning, E-Business, Enterprise Information Systems, and E-Government, 2009. EEEE '09 >A New Intelligent Design Method for Building Material Fatigue S-N Curve
【24h】

A New Intelligent Design Method for Building Material Fatigue S-N Curve

机译:建筑材料疲劳S-N曲线的新型智能设计方法

获取原文

摘要

Abstract -- It is the basis of material fatigue reliability analysis to obtain fatigue S-N curve, The curve is usually obtained from experiment or by fitting many data of loading test basis on three parameters empirical formula, but those methods are complex, high expense and imprecision. In accordance with these disadvantages above methods, a new intelligent method based on common machine learning algorithm (support vector machine) is presented to obtain S-N curve of material fatigue economically and effectively. Complicated and strong nonlinear S-N curve was simulated by design and conformation of support vector machine learning algorithm, compared the errors with output value of the intelligent model, test value and output value from fitting values of three parameters power function, support vector machine learning algorithm had excellent ability of nonlinear modeling and generalization. It gained high precision under limited learning samples and mean relative error is 0.008954%, it provided an economical, practical and reliable approach for material fatigue design.
机译:摘要-获得疲劳SN曲线是材料疲劳可靠性分析的基础,该曲线通常是通过实验获得或通过将多个载荷试验数据拟合为三个参数的经验公式得出,但这些方法复杂,费用高,不精确。针对上述方法的这些缺点,提出了一种基于通用机器学习算法(支持向量机)的智能方法,可以经济有效地获得材料疲劳的S-N曲线。通过支持向量机学习算法的设计与验证,模拟了复杂且强烈的非线性SN曲线,比较了智能模型的输出值,测试值和三参数幂函数拟合值的输出值的误差。出色的非线性建模和泛化能力。在有限的学习样本下获得了较高的精度,平均相对误差为0.008954%,为材料疲劳设计提供了一种经济,实用,可靠的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号