摘要
基于B-P神经网络的原理和方法,利用西南某市1991-2009年的统计数据,建立城市大气SO2浓度预测模型,对西南某市大气SO2浓度进行预测。结果表明,B-P神经网络方法在城市大气SO2浓度预测方面具有合理高效、精确度高、适应力强等特点,值得应用与推广。
Base on the principle and method of B-P neural network,the prediction model of SO2 concentration in urban atmosphere was established by using the statistical data of a city in southwest China from 1991 to 2009,so as to forecast SO2 concentration in urban atmosphere in a city of southwest China.The results showed that B-P neural network applied in the prediction of SO2 concentration in urban atmosphere was reasonable and efficient with high accuracy and wide adaptability,so it was worthy to be popularized.
出处
《安徽农业科学》
CAS
北大核心
2011年第7期4278-4280,共3页
Journal of Anhui Agricultural Sciences
关键词
B-P神经网络
城市大气SO2浓度
预测模型
B-P neural network
SO2 concentration in urban atmospheric
Prediction model
