南京航空航天大学学报（英文版）
南京航空航天大學學報（英文版）
남경항공항천대학학보（영문판）
TRANSACTIONS OF NANJING UNIVERSITY OF AERONATICS & ASTRONAUTICS
2006年
2期
115-119
,共5页
季天剑%安景峰%何申明%李春雷
季天劍%安景峰%何申明%李春雷
계천검%안경봉%하신명%리춘뢰
坡面流%混合料级配%人工神经网络%道路表面水深
坡麵流%混閤料級配%人工神經網絡%道路錶麵水深
파면류%혼합료급배%인공신경망락%도로표면수심
overland flow%gradation of asphalt mixture%artificial neural network%depth of rain water on road surface
建立了基于人工神经网络的道路表面水膜厚度预测模型,通过试验数据的训练确定权重和阈值,经过检验样本的检验,能够很好地预测道路表面的水膜厚度.结果表明,本文建立的人工神经网络模型用于道路表面水膜厚度预估可行.
建立瞭基于人工神經網絡的道路錶麵水膜厚度預測模型,通過試驗數據的訓練確定權重和閾值,經過檢驗樣本的檢驗,能夠很好地預測道路錶麵的水膜厚度.結果錶明,本文建立的人工神經網絡模型用于道路錶麵水膜厚度預估可行.
건립료기우인공신경망락적도로표면수막후도예측모형,통과시험수거적훈련학정권중화역치,경과검험양본적검험,능구흔호지예측도로표면적수막후도.결과표명,본문건립적인공신경망락모형용우도로표면수막후도예고가행.
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.
