Prediction algorithm of PM2.5 mass concentration based on adaptive BP neural network

被引：0
|
作者：
Yegang Chen
机构：
[1] Yangtze Normal University,School of Computer Engineering
来源：
Computing | 2018年 / 100卷
关键词：
PM2.5 mass concentration; Prediction; BP neural network; Pulmonary particulate matter; 65Y05; 62H12;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
PM2.5 hadn’t received much attention until 2013 when people started to understand its dreadful impacts to human health. According to the meteorological monitoring data of PM2.5 from September 9, 2016 to September 9, 2017 in Fuling district, Chongqing, this paper analyzed the impact of temperature, humidity and the power of wind on PM2.5. Using the mathematical model of BP neural networks, a prediction model based on satellite remote sensing data for the pollutant concentration in regional scale was explored, and the forecast for Fuling 3-h PM2.5 concentration was realized. The algorithm effectively establishes the correlation between AOD and PM2.5 concentration, and it suppresses the overfitting phenomenon very well, as well as it makes up the limitation of machine learning for single site prediction.
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页码：825 / 838
页数：13
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