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。

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.

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为此，采用室内人工加速试验方法，研究了石油沥青涂层的老化过程和规律。

The ageing process and regularity of the asphalt coating have been studied with indoor artificial accelerated ageing test.

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采用盐雾和紫外-冷凝室内人工加速老化循环试验的方法，对聚氨酯和丙烯酸两种典型的船壳涂料进行人工加速老化试验。

The degradation of two coatings systems based on polyurethane and acrylic were studied by exposed in UV-condensation chamber and salt-fog chamber alternately.

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