High nonlinear problem which is often met in Chemical engineering, taking the study of tray leakage mode as example, is treated by adopted BP (back propagation) algorithm in artificial neural network.
针对化工中经常遇到的高度非线性问题，以塔板研究中的泄漏模型为例，采用人工神经网络中的BP(反向传播)算法进行处理。
Numerical results indicate that the generalized conforming element has the advantages of high accuracy and uniform convergence to geometrically nonlinear problem of structures.
计算结果表明，广义协调元对于求解结构几何非线性问题同样具有精度高、收敛快等优点。
Because of the high nonlinear of the problem and the complexity of the described physics phenomenon, it is very significative to study them.
由于这类问题的高度非线性以及所描述的物理现象的复杂性，因此这方面的研究是非常有意义的。
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