8 citations as recorded by crossref.

1. Rapid prediction for the transient dispersion of leaked airborne pollutant in urban environment based on graph neural networks X. Shao et al. 10.1016/j.jhazmat.2024.135517
2. Determinants of Spatial Variability of Urban Air Pollutant Concentrations Measured Using a Mobile Laboratory and a Drone L. Järvi et al. 10.2139/ssrn.4094701
3. Introducing new morphometric parameters to improve urban canopy air flow modeling: A CFD to machine-learning study in real urban environments J. Wehrle et al. 10.1016/j.uclim.2024.102173
4. Analyzing Dispersion Characteristics of Fine Particulate Matter in High-Density Urban Areas: A Study Using CFD Simulation and Machine Learning D. Lee et al. 10.3390/land14030632
5. Learning Calibration Functions on the Fly: Hybrid Batch Online Stacking Ensembles for the Calibration of Low-Cost Air Quality Sensor Networks in the Presence of Concept Drift E. Bagkis et al. 10.3390/atmos13030416
6. Control of flow, thermal and pollutant concentration fields by entrainer air streams to improve fresh air quality intake into a semiconductor manufacture/ processing plant T. Liu et al. 10.1016/j.ijft.2022.100211
7. CFD- and BPNN- based investigation and prediction of air pollutant dispersion in urban environment X. Lin et al. 10.1016/j.scs.2023.105029
8. Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets M. Lange et al. 10.5194/gmd-14-7411-2021