... change of air pollutant concentration. In this paper, a short-term forecasting model based on deep learning is proposed for PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration, and the convolutional-based bidirectional gated recurrent unit (CBGRU) method is presented, which combines 1D convnets (convolutional neural networks) and bidirectional GRU (gated recurrent unit) neural networks. The case is carried out by using the Beijing PM2.5 data set in UCI ...
Теги: 1d convolutional neural networks , air pollution forecasting , bidirectional gated recurrent unit , deep learning , air pollution , air pollution control , convolution , deep neural networks , recurrent neural networks , wind , aerodynamic diameters , air pollutant
