Spatial prediction of groundwater potential by various novel boosting-based ensemble learning models in mountainous areas

Spatial prediction of groundwater potential by various novel boosting-based ensemble learning models in mountainous areas

This study makes a significant contribution to the field of groundwater potential mapping (GWPM) by exploring the application of ensemble learning models (ELMs), specifically boosting ensemble models (BEMs), which have not been fully utilized in GWPM. By employing six ELMs (random forest, AdaBoost,...

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Bibliographic Details
Main Authors: Hanxiang Xiong, Xu Guo, Yuzhou Wang, Ruihan Xiong, Xiaofan Gui, Xiaojing Hu, Yonggang Li, Yang Qiu, Jiayao Tan, Chuanming Ma
Format: Article
Language:English
Published: Taylor & Francis Group 2023-10-01
Series:Geocarto International
Subjects:
groundwater potential mapping
ensemble learning models
boosting algorithm
sustainable groundwater management
Online Access:http://dx.doi.org/10.1080/10106049.2023.2274870

Internet

http://dx.doi.org/10.1080/10106049.2023.2274870

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