| 基于B-P神经网络的城市大气SO2浓度预测 |
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| 引用本文： | 王丽梅,袁野,姚建.基于B-P神经网络的城市大气SO2浓度预测[J].安徽农业科学,2011,39(7):4278-4280. |
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| 作者姓名： | 王丽梅 袁野 姚建 |
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| 作者单位： | 1. 四川大学建筑与环境学院,四川 成都,610065
2. 四川省成都市环境监测中心站,四川 成都,610072 |
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| 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。
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| 关 键 词： | B-P神经网络 城市大气SO2浓度 预测模型 |
Prediction of SO2 Concentration in Urban Atmosphere Based on B- P Neural Network |
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| Institution: | WANG Li-mei et al(College of Architecture & Environment,Sichuan University,Chengdu,Sichuan 610065) |
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| Abstract: | 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. |
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| Keywords: | B-P neural network SO2 concentration in urban atmospheric Prediction model |
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