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1 |
Modelling seawater <italic>p</italic>CO<sub>2</sub> and pH in the Canary Islands region based on satellite measurements and machine learning techniques
Enthalten in Ocean science Bd. 22, 2026, Nr. 1: 609-628. 20 S.
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2 |
Improving snow water equivalent modelling: a comparative study of hybrid machine learning techniques
Enthalten in The Cryosphere Bd. 20, 2026, Nr. 2: 1427-1444. 18 S.
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3 |
Sustainable prediction of compression index in fine-grained soils using machine learning techniques
Enthalten in Open Geosciences Bd. 18, 2026, Nr. 1. 19 S.
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4 |
Leveraging Machine Learning techniques and SEVIRI data to detect volcanic clouds composed of ash, ice, and SO<sub>2</sub>
Enthalten in EGUsphere 23.02.2026: 1-26. 26 S.
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5 |
Retraction Note: A novel algorithm for the construction of fast English sentence retrieval model using a combination of ontology and advanced machine learning techniques
Enthalten in Soft computing 5.1.2026: 1
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6 |
A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development
Tu, Hsing-Fen. - Reutlingen : Hochschule Reutlingen, 2025
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7 |
Evaluating Recycling Initiatives for Landfill Diversion in Developing Economies Using Integrated Machine Learning Techniques
Adedara, Muyiwa Lawrence. - Kiel : Universitätsbibliothek Kiel, 2025
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8 |
Forecasting of residential unit's heat demands: a comparison of machine learning techniques in a real-world case study
Kemper, Neele. - Augsburg : Universität Augsburg, 2025
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9 |
TiAlNb alloy interatomic potentials: comparing passive and active machine learning techniques with MTP and DeePMD
Chandran, Anju. - Hamburg : Technische Universität Hamburg. Universitätsbibliothek, 2025
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10 |
Modeling density of carbon dioxide-saturated polyethylene glycol using machine learning techniques
Enthalten in Journal of polymer engineering Bd. 45, 2025, Nr. 8: 660-673. 14 S.
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