Forecasting Fine Particulate Matter Concentrations by In-Depth Learning Model According to Random Forest and Bilateral Long- and Short-Term Memory Neural Networks
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- Jianzhou Wang & Tong Niu & Rui Wang, 2017. "Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model," IJERPH, MDPI, vol. 14(3), pages 1-33, March.
- Lili Du & Yan Wang & Zhicheng Wu & Chenxiao Hou & Huiting Mao & Tao Li & Xiaoling Nie, 2019. "PM 2.5 -Bound Toxic Elements in an Urban City in East China: Concentrations, Sources, and Health Risks," IJERPH, MDPI, vol. 16(1), pages 1-13, January.
- Sang Won Choi & Brian H. S. Kim, 2021. "Applying PCA to Deep Learning Forecasting Models for Predicting PM 2.5," Sustainability, MDPI, vol. 13(7), pages 1-30, March.
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- Yadong Pei & Chiou-Jye Huang & Yamin Shen & Yuxuan Ma, 2022. "An Ensemble Model with Adaptive Variational Mode Decomposition and Multivariate Temporal Graph Neural Network for PM2.5 Concentration Forecasting," Sustainability, MDPI, vol. 14(20), pages 1-22, October.
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Keywords
Chinese regions; variable selection; meteorological factors; BiLSTM; prediction;All these keywords.
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