本文采用动态小波神经网络方法，对复合材料疲劳剩余寿命进行了预测，结果与试验结果很接近。
The dynamic wavelet neural network method is applied to predict the fatigue residual life of the composite material. The predicting result is very close to the testing result.
综合比较了核机器方法与人工神经网络法的预测效果，同时展示了常规核与复合核的性能对比。
Experiment results show that, kernel machine method is better than artificial neural network, and compound kernel functions is better than common single kernel functions.
以同样方法对复合氨基酸注射液进行测定，通过训练好的网络进行色氨酸、酪氨酸含量的计算，相对误差分别为4.0％和2.6％。
The method has been applied to the determination of tryptophan and tyrosine in compound amino acid injection, and the relative errors were 4.0% and 2.6% .
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