【摘要】 在使用径向基神经网络建立注塑工艺模型时,虽然能够得到较好的模型,但是建模时训练样本数量将会对模型的质量产生较大的影响。本研究对建模所需的原始样本数据首先进行信息扩散处理,然后再使用径向基神经网络建立注塑工艺参数与塑件沉降斑指数之间的模型。从结果上看,在注塑训练样本数量相同的情况下,运用该方法均可以得到优于仅使用普通径向基网络构建的模型。更多还原

【Abstract】 Although RBF neural network was widely used to uncover the relationship between injection molding process parameters and part quality,which could generate high quality models,the number of training samples was a nonnegligible factor which seriously affected the accuracy of the injection model. In this paper,the information diffusion theory is applied to derive new patterns,which were used to generate sink model with RBF neural network,from original training samples. The results showed that this method could generate better injection model when the training samples were equal.更多还原