📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Advancing neural network-based data assimilation for large-scale spatiotemporal systems with sparse observations (2024)

First Author: Cai S

Attributed to: Hybrid AI and multiscale physical modelling for optimal urban decarbonisation combating climate change funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1063/5.0228384

Publication URI: http://dx.doi.org/10.1063/5.0228384

Type: Journal Article/Review

Parent Publication: Physics of Fluids

Issue: 9