GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea-Reference-Cited by-同舟云学术

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GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea

Published:2017-03-28 Issue:8 Volume:33 Page:847-861
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Lee Saro¹²^ORCID,Hong Soo-Min³,Jung Hyung-Sup⁴^ORCID

Affiliation:

1. Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, Korea

2. Department of Geophysical Exploration, Korea University of Science and Technology, Daejeon, Korea

3. Department of English Language and Literature, University of Seoul, Seoul, Korea

4. Department of Geoinformatics, University of Seoul, Seoul, Korea

Funder

National Research Foundation of Korea

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2017.1303091

Reference51 articles.

1. Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool – A case of predicting potential zones of sustainable groundwater resources

2. Introduction Neural networks in remote sensing

3. Groundwater recharge study in arid region: An approach using GIS techniques and numerical modeling

4. Integrated remote sensing and GIS‐based approach for assessing groundwater potential in West Medinipur district, West Bengal, India

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