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The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Methods used for handling and quantifying model uncertainty of artificial neural network models for air pollution forecasting

Lookup NU author(s): Dr Sheen Cabaneros

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Publication metadata

Author(s): Cabaneros SM, Hughes B

Publication type: Review

Publication status: Published

Journal: Environmental Modelling & Software

Year: 2022

Volume: 158

Print publication date: 01/12/2022

Online publication date: 24/09/2022

Acceptance date: 13/09/2022

ISSN (print): 1364-8152

ISSN (electronic): 1873-6726

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.envsoft.2022.105529

DOI: 10.1016/j.envsoft.2022.105529

ePrints DOI: 10.57711/tzx0-z614


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