An Overview of Machine Learning Techniques for Sediment Prediction-Reference-Cited by-同舟云学术

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An Overview of Machine Learning Techniques for Sediment Prediction

Published:2023-12-06 Issue: Volume:133 Page:204
ISSN:
Container-title:The 4th International Electronic Conference on Applied Sciences
language:
Short-container-title:

Author:

Nda Muhammad¹^ORCID,Adnan Mohd Shalahuddin²,Yusoff Mohd Azlan Bin Mohd²^ORCID,Nda Ramatu Muhammad³

Affiliation:

1. Department of Civil Engineering, The Federal Polytechnic Bida, Bida 912211, Niger State, Nigeria

2. Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Johor, Malaysia

3. Faculty of Computing and Information Technology, Newgate University Minna, Minna 920101, Niger State, Nigeria

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/56/1/204/pdf

Reference40 articles.

1. Machine learning approach to modeling sediment transport;Bhattacharya;J. Hydraul. Eng.,2007

2. Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins;Atieh;J. Hydrol.,2015

3. Davis, B.E. (2023, September 08). A Guide to the Proper Selection and Use of Federally Approved Sediment and Water-Quality Samplers. U.S. Geological Survey, Open File Report 2005-1087, Available online: https://pubs.usgs.gov/of/2005/1087/.

4. Edwards, T.K., and Glysson, G.D. (1999). Field Methods for Measurement of Fluvial Sediment.

5. Larsen, M.C. (July, January 27). Fluvial Sediment in the Environment: A National Challenge. Proceedings of the 9th Federal Interagency Sedimentation Conference, Las Vegas, NV, USA.

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