Resampling-driven machine learning models for enhanced high streamflow forecasting

Resampling-driven machine learning models for enhanced high streamflow forecasting

Accurate forecasting of high streamflow remains a significant challenge and is essential for sustainable water resource management and disaster mitigation, particularly due to the data imbalance often present during model development. This study proposes novel hybrid models through a comprehensive i...

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Bibliographic Details
Main Authors: Nureehan Salaeh, Sirimon Pinthong, Warit Wipulanusat, Uruya Weesakul, Jakkarin Weekaew, Quoc Bao Pham, Pakorn Ditthakit
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2026-01-01
Series:Water Cycle
Subjects:
High-streamflow
Hybrid model
Imbalanced data
Recursive forecasting
Resampling method
Online Access:http://www.sciencedirect.com/science/article/pii/S2666445325000340
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http://www.sciencedirect.com/science/article/pii/S2666445325000340

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