This review outlines historical and recent research progress on the accuracy of
computational fluid dynamics (CFD) simulations of urban aerodynamics and microclimates …

Abstract Machine learning (ML) is increasing in popularity in the field of weather and climate
modelling. Applications range from improved solvers and preconditioners, to …

The classical development of neural networks has primarily focused on learning mappings
between finite dimensional Euclidean spaces or finite sets. We propose a generalization of …

With massive advancements in sensor technologies and Internet-of-things (IoT), we now
have access to terabytes of historical data; however, there is a lack of clarity on how to best …

神经网络作为一种强大的信息处理工具在计算机视觉, 生物医学, 油气工程领域得到广泛应用,
引发多领域技术变革. 深度学习网络具有非常强的学习能力, 不仅能发现物理规律 …

Abstract Sparse Identification of Nonlinear Dynamics (SINDy) is a method of system
discovery that has been shown to successfully recover governing dynamical systems from …

The Boltzmann equation with the Bhatnagar-Gross-Krook collision model (Boltzmann-BGK
equation) has been widely employed to describe multiscale flows, ie, from the hydrodynamic …

Being a primary contributor to global energy consumption and energy-related carbon
emissions, the building and building construction sectors are a crucial player in the …

Well known to the machine learning community, the random feature model is a parametric
approximation to kernel interpolation or regression methods. It is typically used to …

With massive advancements in sensor technologies and Internet-of-things, we now have
access to terabytes of historical data; however, there is a lack of clarity in how to best exploit …