Comparing three machine learning algorithms with existing methods for natural streamflow estimation
Author:
Affiliation:
1. Département de génie civil et de génie du bâtiment, Université de Sherbrooke, Sherbrooke, Quebec, Canada
2. Department of Environment and Climate Change, Ontario Power Generation, Niagara-on-the-Lake, Ontario, Canada
Funder
NSERC
Publisher
Informa UK Limited
Subject
Water Science and Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/02626667.2023.2273402
Reference66 articles.
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2. Alpaydin, E., 2020. Introduction to machine learning. Cambridge, MA: MIT press.
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4. LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT
5. Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches
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