Comparative study of machine learning methods and GR2M model for monthly runoff prediction

Comparative study of machine learning methods and GR2M model for monthly runoff prediction

Monthly runoff time-series estimation is imperative information for water resources planning and development projects. This article aims to comparatively investigate the applicability of machine learning (ML) methods (i.e., Random Forest (RF), M5 model tree (M5), Support Vector Regression with polyn...

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Bibliographic Details
Main Authors: Pakorn Ditthakit, Sirimon Pinthong, Nureehan Salaeh, Jakkarin Weekaew, Thai Thanh Tran, Quoc Bao Pham
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:Ain Shams Engineering Journal
Subjects:
GR2M
M5 Model tree
Random forest
Runoff
Support vector regression
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447922002520

Internet

http://www.sciencedirect.com/science/article/pii/S2090447922002520

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