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.
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.
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.
并根据不同的试验标准进行了两种人工气候老化试验，比较了这两种方法与自然气候暴露试验结果的相关性。
Two artificial weathering tests were conducted according to different standards, and correlations between outdoor exposure test and artificial weathering tests were compared.
并根据不同的试验标准进行了两种人工气候老化试验，比较了这两种方法与自然气候暴露试验结果的相关性。
Two artificial weathering tests were conducted according to different standards, and correlations between outdoor exposure test and artificial weathering tests were compared.
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