期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：300
期号：3
页码：1-6
DOI：10.1088/1755-1315/300/3/032090
出版社：IOP Publishing
摘要：In order to accurately predict the concentration of air pollutants in Shanghai, a prediction model of the concentration of air pollutants in Shanghai based on Wavelet Transform and Long Short-Term Memory (LSTM) was established to predict the concentration of six air pollutants in Shanghai. Firstly, the historical time series of daily air pollutant concentration is decomposed into different frequencies by wavelet decomposition transform and recombined into a set of high-dimensional training data. Secondly, LSTM prediction model is trained with high-dimensional data sets, and parameters are adjusted repeatedly to obtain the optimal prediction model. The results show that the combined model is more accurate than the traditional LSTM model in predicting pollutant concentration.
