Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/30477
Title: | Training stiff neural ordinary differential equations in data-driven wastewater process modelling |
Authors: | Huang, X Kandris, K Katsou, E |
Issue Date: | 30-Dec-2024 |
Publisher: | Elsevier |
Citation: | Huang, X., Kandris, K, and Katsou, E. (2025) 'Training stiff neural ordinary differential equations in data-driven wastewater process modelling', Journal of Environmental Management, 373, 123870, pp. 1 - 14. doi: 10.1016/j.jenvman.2024.123870 |
Abstract: | Highlights: • Introduce a novel normalisation pair method for training of stiff neural ODEs. • Propose incremental training strategy for enhance performance. • Provide a foundation for broad application of neural ODEs. |
Description: | Data availability:
I have shared the link of my data/code in the manuscript uploaded. Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S030147972403857X?via%3Dihub#appsec1 . |
URI: | https://bura.brunel.ac.uk/handle/2438/30477 |
DOI: | https://doi.org/10.1016/j.jenvman.2024.123870 |
ISSN: | 0301-4797 |
Other Identifiers: | ORCiD: Xiangjun Huang https://orcid.org/0000-0001-9020-3490 ORCiD: Kyriakos Kandris https://orcid.org/0000-0003-4173-955X ORCiD: Evina Katsou https://orcid.org/0000-0002-2638-7579 123870 |
Appears in Collections: | Dept of Civil and Environmental Engineering Research Papers |
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FullText.pdf | Copyright © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license ( https://creativecommons.org/licenses/by/4.0/ ). | 15.47 MB | Adobe PDF | View/Open |
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