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DEPTH PREDICTION OF RAIN WATER ON ROAD SURFACE BASED ON ARTIFICIAL NEURAL NETWORK 被引量:2
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作者 季天剑 安景峰 +1 位作者 何申明 李春雷 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2006年第2期115-119,共5页
A model based on the non-linear artificial neural network (ANN) is established to predict the thickness of the water film on road surfaces. The weight and the threshold can be determined by training test data, and t... A model based on the non-linear artificial neural network (ANN) is established to predict the thickness of the water film on road surfaces. The weight and the threshold can be determined by training test data, and the water film thickness on the road surface can be accurately predicted by the empirical verification based on sample data. Results show that the proposed ANN model is feasible to predict the water film thickness of the road surface. 展开更多
关键词 overland flow gradation of asphalt mixture artificial neural network depth of rain water on road surface
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