Pedestrian level wind flow field of elevated tall buildings with dense tandem arrangement H Gao, J Liu, P Lin, C Li, Y Xiao, G Hu Building and Environment 226, 109745, 2022 | 13 | 2022 |
Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables W Jiang, B Liu, Y Liang, H Gao, P Lin, D Zhang, G Hu Applied Energy 353, 122155, 2024 | 9 | 2024 |
A novel hybrid deep learning model for multi-step wind speed forecasting considering pairwise dependencies among multiple atmospheric variables W Jiang, P Lin, Y Liang, H Gao, D Zhang, G Hu Energy 285, 129408, 2023 | 6 | 2023 |
An optimal sensor placement scheme for wind flow and pressure field monitoring H Gao, J Liu, P Lin, G Hu, L Patruno, Y Xiao, KT Tse, KCS Kwok Building and Environment 244, 110803, 2023 | 4 | 2023 |
Numerical study of flow characteristics of tornado-like vortices considering both swirl ratio and aspect ratio D Zhang, Z Liu, X Jiang, W Jiang, H Gao, C Li, Y Xiao, G Hu Journal of Wind Engineering and Industrial Aerodynamics 240, 105468, 2023 | 3 | 2023 |
Urban wind field prediction based on sparse sensors and physics‐informed graph‐assisted auto‐encoder H Gao, G Hu, D Zhang, W Jiang, KT Tse, KCS Kwok, A Kareem Computer‐Aided Civil and Infrastructure Engineering, 2024 | 2 | 2024 |
A novel spatio-temporal wind speed forecasting method based on the microscale meteorological model and a hybrid deep learning model D Zhang, G Hu, J Song, H Gao, H Ren, W Chen Energy 288, 129823, 2024 | 1 | 2024 |
Advancing storm surge forecasting from scarce observation data: A causal-inference based Spatio-Temporal Graph Neural Network approach W Jiang, J Zhang, Y Li, D Zhang, G Hu, H Gao, Z Duan Coastal Engineering 190, 104512, 2024 | | 2024 |
Numerical study of dynamic amplification factor and characteristic wind curves of high-speed train in tornado-like vortices D Zhang, B Liu, Y Liang, W Jiang, H Gao, J Zhang, G Hu Journal of Wind Engineering and Industrial Aerodynamics 247, 105707, 2024 | | 2024 |
Prediction of wind fields in mountains at multiple elevations using deep learning models H Gao, G Hu, D Zhang, W Jiang, H Ren, W Chen Applied Energy 353, 122099, 2024 | | 2024 |