在工程应用中经常会遇到一些复杂的非线性系统，这些系统状态方程复杂，难以用数学方 法准确建模。在这种情况下，可以建立 BP 神经网络表达这些非线性系统。该方法把未知系统看成是一个黑箱，首先用系统输入输出数据训练 BP 神经网络，使网络能够表达该未知函数，然后用训练好的 BP 神经网络预测系统输出 。(In engineering applications, some complicated nonlinear systems are often encountered. The equations of state of these systems are complex and difficult to model accurately by mathematical methods. In this case, BP neural networks can be established to express these nonlinear systems. The unknown system is regarded as a black box, first with the system input and output data to train the BP neural network, the network can express the unknown function, and then use the trained BP neural network to predict the output of the system.)