Optimising Venturi flume oxygen transfer efficiency using uncertainty-aware decision trees
© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).
Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 90(2024), 12 vom: 29. Dez., Seite 3210-3240 |
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Format: | Article en ligne |
Langue: | English |
Publié: |
2024
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Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research |
Sujets: | Journal Article MNLR) Shapley analysis Venturi flume machine learning (ML) and flume design parameters ( regression analysis (MLR standard oxygen transfer efficiency (SOTE) uncertainty analysis Oxygen S88TT14065 |
Accès en ligne |
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