📣 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.

Predicting the effects of environmental parameters on the spatio-temporal distribution of the droplets carrying coronavirus in public transport - A machine learning approach (2022)

First Author: Mesgarpour M

Attributed to: Risk EvaLuatIon fAst iNtelligent Tool (RELIANT) for COVID19 funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1016/j.cej.2021.132761

PubMed Identifier: 34642569

Publication URI: http://europepmc.org/abstract/MED/34642569

Type: Journal Article/Review

Parent Publication: Chemical Engineering Journal

ISSN: 1385-8947