Article
PM2.5 concentration prediction using weighted CEEMDAN and improved LSTM neural network.
Environmental science and pollution research international - 1 Jun 2023
Zhang Li, Liu Jinlan, Feng Yuhan, Wu Peng, He Pengkun
Abstract excerpt
As the core of pollution prevention and management, accurate PM2.5 concentration prediction is crucial for human survival. However, due to the nonstationarity and nonlinearity of PM2.5 concentration data, the accurate prediction for PM2.5 concentration remains a challenge. In this study, a PM2.5 concentration prediction method using weighted complementary ensemble empirical mode decomposition with adaptive noise...
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