Finally, taking data from CAE as samples; the BP neural network of warping-shrinkage prediction model is established by designing the network structure and selection of learning algorithm.
最后以数值仿真得到的数据为样本数据，通过设计网络结构和选用学习算法，建立并得到基于BP人工神经网络的翘曲——收缩预测模型。
A prastical neural network of BP model is acquired after trained with a learning samples set, which consists of materials selection knowledge.
利用训练样本使一个BP神经网络学习选择材料的知识，利用测试样本验证此网络的能力。
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