By using some road traffic noise measured data, a model of neural network for road traffic noise prediction was established.
本文通过分析影响公路交通噪声的各种因素，并利用实测样本数据，建立了一个公路交通噪声预测的神经网络模型。
Through comparing various domestic and international traffic noise prediction models, a revised forecast model was selected to predict theoretical noise value.
在比较国内外各种道路交通噪声预测模型特点的基础上，选择了一种修正预测模型，预测出理论噪声值。
Now the FHWA model used in traffic noise prediction get the number and type of vehicles by artificial way, the labor cost is high and the statistical value often not very accuracy.
目前交通噪声预测使用的FHWA模型在实际应用以人工方式来统计通过的车辆数和车型，人工成本高，统计值容易产生偏差。
Highway traffic noise prediction model is deduced and analyzed. It is indicated that the FHWA model originating from USA Federal Highway Administration is an approximate representation.
对公路交通噪声预测模型进行了分析推导，指出美国联邦公路局FHWA模型为近似表达式，并给出了精确表达式。
The research integrates the prediction of traffic noise into the geography information system, and designs and develops the urban road traffic noise prediction system which is based on the GIS.
本研究在地理信息系统集成了交通噪声预测模型的基础上，设计和开发了基于地理信息系统的城市道路交通噪声预测系统。
Traffic noise assessment and prediction system has been used in Huizhou, and get a favorable efficient.
交通噪声评价和预测系统已应用于惠州市交通噪声污染现状评价及预测，并取得了良好的效果。
Road traffic noise in a sample housing estate was assessed using prediction method and based on collected traffic flow and vehicle type data.
根据实测所得交通流量和车型分布，采用预测为主、实测为辅的方法对典型居住小区进行了交通噪声预测与评价。
Road traffic noise in a sample housing estate was assessed using prediction method and based on collected traffic flow and vehicle type data.
根据实测所得交通流量和车型分布，采用预测为主、实测为辅的方法对典型居住小区进行了交通噪声预测与评价。
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