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      Enhancing sediment transport predictions through machine learning-based multi-scenario regression models

      Author(s): , , , ,
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      Journal: Results in Engineering
      Publisher: Elsevier BV

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          Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines

          M. Chica-Olmo, V. Rodriguez-Galiano, M. Sanchez-Castillo … (2015)
          Article 0 comments Cited 166 times – based on 0 reviews     Review now
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            A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions

            Andreas Krause, Maarten Speekenbrink, Eric Schulz (2018)
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              The impacts of fine sediment on riverine fish

              Paul J. Kemp, David Sear, Adrian L Collins … (2011)
              Article 0 comments Cited 107 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Ali Najah Ahmed: (View ORCID Profile)
                Journal
                Title: Results in Engineering
                Abbreviated Title: Results in Engineering
                Publisher: Elsevier BV
                ISSN (Print): 25901230
                Publication date Created: December 2023
                Publication date (Print): December 2023
                Volume: 20
                Page: 101585
                Article
                DOI: 10.1016/j.rineng.2023.101585
                SO-VID: 5c3f0c04-038c-4059-91ed-69dddc4d3bf1
                Copyright © © 2023
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                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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