most citedUsing Diffusion Models for Reducing Spatiotemporal Errors of Deep Learning Based Urban Microclimate Predictions at Post-Processing Stage

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025

Generalization of Urban Wind Environment Using Fourier Neural Operator Across Different Wind Directions and Cities

Cheng Chen, Geng Tian, Shaoxiang Qin +6

Simulation of urban wind environments is crucial for urban planning, pollution control, and renewable energy utilization. However, the computational requirements of high-fidelity c…

physics.flu-dyn2025★ 2 cited

Using Diffusion Models for Reducing Spatiotemporal Errors of Deep Learning Based Urban Microclimate Predictions at Post-Processing Stage

Sepehrdad Tahmasebi, Geng Tian, Shaoxiang Qin +3

Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are comp…

physics.flu-dyn2024★ 1 cited

Modeling Multivariable High-resolution 3D Urban Microclimate Using Localized Fourier Neural Operator

Shaoxiang Qin, Dongxue Zhan, Dingyang Geng +6

Accurate urban microclimate analysis with wind velocity and temperature is vital for energy-efficient urban planning, supporting carbon reduction, enhancing public health and comfo…