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Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province, Vietnam.
Authors: Hoang Phan Hai Yen, Pham Thai Binh, Tran Van Phong, Dương Hai Ha, Romulus Costache, Le Van Hiep, Nguyen Huu Duy, Mahdis Amiri, Nguyen Van Tao, Indra Parakash
154    0
Geoscience Frontiers
: 63     : 1-15
: https://doi.org/10.1016/j.ecoinf.2021.101292
: 1048-bai-so-1-q1.pdf
Publishing year: 2/2021
Gia Lai is a mountainous province greatly affected by drought. Water shortage occurs in the dry season, causing thousands of hectares of agricultural land to be damaged. Surface water sources are unevenly distributed in the province, not ensuring the sustainability and development of the region. Therefore, building a map of groundwater potential for agricultural production development and the lives of mountainous people is considered a mandatory task for appropriate water resource management in the province. . This paper uses a number of machine learning models to map groundwater potential and model spatial distribution of groundwater in Gia Lai province.
Locally weighted learning, Hybrid models, Groundwater Potential, GIS, Vietnam
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