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中文摘要: 近年来将BP网络模型应用到大气污染浓度预报中,并建立了大气污染物浓度的神经网络预报模型。将计算结果与监测值进行了验证,结果表明:TSP的计算值与观测值之间的绝对误差为4×10-3～3×10-2mg·m-3,NOX 的计算值与观测值之间的绝对误差为5×10-3～2×10-2mg·m-3;且具有较好的相关性。BP模型是目前最为广泛应用的神经网络模型之一,它是一
中文关键词: 人工神经网络，BP模型，大气污染预报
Abstract:Recent years, BP model has been applied to atmospheric pollution forecast, a neural network prediction model of atmospheric pollutant concentration is set up. The research results show: the absolute errors of TSP between calculating and the monitoring is from 4×10-3mg·m-3to 3×10-2mg·m-3, the absolute errors of NOX between the calculating and the monitoring is from 5×10-3mg·m -3 to 2×10-2mg·m-3. The correlation between results of calculating and the monitoring is very well. As one of the neural network models, BP model has been applied widely, which is a simple and effective algorithm.So, BP neural network model has supplied a new way for the air pollution forecast.
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引用文本：
马雁军,杨洪斌,张云海,2003.BP神经网络法在大气污染预报中的应用研究[J].气象,29(7):49-51.
,2003.Study on Prediction of Atmosphere Pollution Concentration Based on BP Model[J].Meteor Mon,29(7):49-51.
马雁军,杨洪斌,张云海,2003.BP神经网络法在大气污染预报中的应用研究[J].气象,29(7):49-51.
,2003.Study on Prediction of Atmosphere Pollution Concentration Based on BP Model[J].Meteor Mon,29(7):49-51.