摘要
依据BP神经网络系统能够利用人工智能的方法,准确分析多变量非线性系统的特性,采用多层向前BP神经网络系统建立起了橡胶老化预报模型。并利用此模型计算分析了丁基硫化橡胶基于温度与时间老化预报。结果表明,模型计算与实验在结果上有较好的一致性。
Based on characteristics of BP neural network which can precisely analyze multi-variable nonlinear systems using artificial intelligence, in this paper, we proposed model for predicting rubber aging. Moreover, the data of aging of butyl rubber vulcanizate have been calculated and analyzed by means of this method. The result showed that there is a good agreement between prediction of model and experiment.
出处
《合成材料老化与应用》
2003年第2期27-30,48,共5页
Synthetic Materials Aging and Application
