PM2.5 concentration prediction using deep learning in internet of things air monitoring system
Wei Bai, Fengying Li
Environmental Engineering Research. 2023;28(1):210456  Published online 2022 Feb 21     DOI: https://doi.org/10.4491/eer.2021.456
Citations to this article as recorded by Crossref logo
A new attention-based CNN_GRU model for spatial–temporal PM2.5 prediction
Sara Haghbayan, Mehdi Momeni, Behnam Tashayo
Environmental Science and Pollution Research.2024; 31(40): 53140.     CrossRef
Statistical and machine learning approaches for estimating pollution of fine particulate matter (PM2.5) in Vietnam
Tuyet Nam Thi Nguyen, Tan Dat Trinh, Pham Cung Le Thien Vu, Pham The Bao
Journal of Environmental Engineering and Landscape.2024; 32(4): 292.     CrossRef
Enhanced Sequence-to-Sequence Attention-Based PM2.5 Concentration Forecasting Using Spatiotemporal Data
Baekcheon Kim, Eunkyeong Kim, Seunghwan Jung, Minseok Kim, Jinyong Kim, Sungshin Kim
Atmosphere.2024; 15(12): 1469.     CrossRef
Super-hydrophobic blended needle-punched nonwovens integrated with silica-aerogels for PM2.5 filtration
Hanur Meku Yesuf, Syed Rashedul Islam, Xueping Zhang, Xiaohong Qin
Environmental Engineering Research.2024; 30(3): 240404.     CrossRef
Short Path Wind-Field Distance-Based Lagrangian Trajectory Model for Enhancing Atmospheric Dispersion Prediction Accuracy
Soukaina R’Bigui, Hind R’Bigui, Chiwoon Cho
IEEE Access.2023; 11: 106465.     CrossRef
Adaptive scalable spatio-temporal graph convolutional network for PM2.5 prediction
Qingjian Ni, Yuhui Wang, Jiayi Yuan
Engineering Applications of Artificial Intelligenc.2023; 126: 107080.     CrossRef
A Prediction Hybrid Framework for Air Quality Integrated with W-BiLSTM(PSO)-GRU and XGBoost Methods
Wenbing Chang, Xu Chen, Zhao He, Shenghan Zhou
Sustainability.2023; 15(22): 16064.     CrossRef