A New Approach Based on Deep Neural Networks and Multisource Geospatial Data for Spatial Prediction of Groundwater Spring Potential-Reference-Cited by-同舟云学术

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A New Approach Based on Deep Neural Networks and Multisource Geospatial Data for Spatial Prediction of Groundwater Spring Potential

Published:2024 Issue: Volume:12 Page:26344-26363
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Nhu Viet-Ha¹^ORCID,Phan Duong Cao²^ORCID,Hoa Pham Viet³,Vinh Pham The⁴^ORCID,Bui Dieu Tien⁵^ORCID

Affiliation:

1. Department of Geological-Geotechnical Engineering, Hanoi University of Mining and Geology, Bac Tu Liem, Hanoi, Vietnam

2. Centre for AI and Applied Data Analytics, School of Computer Science, University College Dublin, Belfield, Ireland

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

4. Center of Environmental Technology Science and Ecology, Southern Institute of Water Resources Research, Ho Chi Minh City, Vietnam

5. Department of Business and IT, GIS Group, University of South-Eastern Norway, Bø, Telemark, Norway

Funder

Ministry of Education and Training (MoET), Vietnam

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10416842.pdf?arnumber=10416842

Reference110 articles.

1. Environmental Processes and Management

2. Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization

3. South Asian agriculture increasingly dependent on meltwater and groundwater

4. Review: Advances in groundwater potential mapping

5. Mapping of regional potential groundwater springs using Logistic Regression statistical method

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