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将支持向量机应用于挤出吹塑过程的一段型坯壁厚分布的预测,并将预测结果与人工神经网络预测的结果进行比较,验证了支持向量机具有更强的泛化能力。
The application of SVM to the prediction of the wall thickness distribution of a section of parison in extrusion blow molding process is compared with that predicted by artificial neural network. The results show that SVM has stronger generalization ability.