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采用人工神经网络方法，将８１组实验数据用于神经网络的建模及检测，建立了液态挤压成形管、棒材工艺参数知识库，可以对该工艺的关键参数进行较为准确的预测，从而为推动该金属成形新工艺的实际应用奠定了基础。
Using the artificial neural network method, 81 sets of experimental data are used in the modeling and testing of the neural network, and the knowledge base of liquid extrusion forming tube and bar material parameters is established, which can predict the key parameters of the process more accurately This laid the foundation for the practical application of the new metal forming process.