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WU Qi-hao, JIANG Xin-quan, MA Xiao-li, CHEN Ping, CHEN Jing-run. CORRELATION ANALYSIS OF HEAVY METAL POLLUTION AND MAGNETIC SUSCEPTIBILITY IN SOIL OF A SEWAGE IRRIGATION AREA[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(9): 231-235,174. doi: 10.13205/j.hjgc.202009037
Citation: ZHOU Jianguo, WANG Jianyu, WEI Siti. PREDICTION OF PM2.5 AND OZONE CONCENTRATION BASED ON VMD-CEEMD DECOMPOSITION AND LSTM[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(6): 157-165,221. doi: 10.13205/j.hjgc.202306021

PREDICTION OF PM2.5 AND OZONE CONCENTRATION BASED ON VMD-CEEMD DECOMPOSITION AND LSTM

doi: 10.13205/j.hjgc.202306021
  • Received Date: 2022-09-13
    Available Online: 2023-09-02
  • Accurate prediction of ozone and PM2.5 concentration can provide a scientific basis for the prevention and control of photochemical pollution. However, the prediction accuracy of the existing ozone and PM2.5 concentration prediction models is still not sufficient. Based on the daily average ozone and PM2.5 concentration data in Nanjing from January 1, 2015, to June 30, 2021, a pollutant concentration prediction model for complementary ensemble empirical mode decomposition (CEEMD) secondary decomposition and long and short-term memory neural network (LSTM) was constructed. Firstly, the ozone and PM2.5 concentration sequence was decomposed by variational mode decomposition (VMD). Secondly, the CEEMD secondary decomposition was used with residual components, and then all the decomposed subsequences were predicted by LSTM. Finally, the output result was reconstructed to get the final result. The results showed that for the forcast of PM2.5 and O3 concentration in Nanjing, comparing with the other models, the model VMD-CEEMD-LSTM proposed in this paper was superior and robust, with the RMSE of ozone and PM2.5 concentrations of 16.47 and 5.12, respectively. This study could provide valuable references for analyzing ozone and PM2.5 pollution trend.
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