摘要
通过构造反向传播神经网络，对疲劳实验曲线进行学习，实现由神经网络表示的多维函数逼近。此种学习是一个慢速过程，但由这一逼近预测得出疲劳曲线则是一个快速过程。拟合结果表明，这一方法十分有效、稳定，便于使用。
Multidimensional funetion approximation of fatigue experimental curves is achieved by applying neural network techniques.The constructed Back-Propagation Neural Network(BPNN) learns these curves by using leaming algorithm,and this sort of leaming is a long time process.After BPNN has learned the curves suceessfully,the prediction of new curves will pro- ceed with short time. The prediction process can be linked very easily with fatigue life pxediction program. The results of fitting show that the method is verv effective,stable and convenient.
出处
《航空学报》
EI
CAS
CSCD
北大核心
1994年第3期359-361,共3页
Acta Aeronautica et Astronautica Sinica
基金
航空科学基金
关键词
疲劳
神经网
函数分析
fatigue(materials),neural nets,function analvsis
