A tree-based intelligence ensemble approach for spatial prediction of potential groundwater-Reference-Cited by-同舟云学术

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A tree-based intelligence ensemble approach for spatial prediction of potential groundwater

Published:2020-01-28 Issue:12 Volume:13 Page:1408-1429
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Avand Mohammadtaghi¹^ORCID,Janizadeh Saeid¹,Tien Bui Dieu²³,Pham Viet Hoa⁴,Ngo Phuong Thao T.⁵,Nhu Viet-Ha⁶

Affiliation:

1. Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Tehran, Iran

2. Geographic Information Science Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam

3. Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam

4. Ho Chi Minh City Institute of Resources Geography, Vietnam Academy of Science and Technology, Ho Chi Minh City, Vietnam

5. Institute of Research and Development, Duy Tan University, Da Nang, Vietnam

6. Department of Geological-Geotechnical Engineering, Hanoi University of Mining and Geology, Hanoi, Vietnam

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2020.1718785

Reference121 articles.

1. Evaluating digital terrain indices for soil wetness mapping – a Swedish case study

2. Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

3. Groundwater Overexploitation and Seawater Intrusion in Coastal Areas of Arid and Semi-Arid Regions

4. Robust ensemble learning framework for day-ahead forecasting of household based energy consumption

5. Permutation importance: a corrected feature importance measure

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