Modeling geothermal energy potential zones in the Bertoua region and surroundings with machine learning using descent gradient based on linear-regression model (Eastern Cameroon)-Reference-Cited by-同舟云学术

Modeling geothermal energy potential zones in the Bertoua region and surroundings with machine learning using descent gradient based on linear-regression model (Eastern Cameroon)

Published:2024-06-14 Issue:4 Volume:10 Page:5293-5308
ISSN:2363-6203
Container-title:Modeling Earth Systems and Environment
language:en
Short-container-title:Model. Earth Syst. Environ.

Author:

Chiewo Ceukou Téthys-Authie,Owona Angue Marie-Louise-Clotilde,Moustapha Ndam Njikam Mohamed

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s40808-024-02064-6.pdf

Reference67 articles.

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2. Abraham E, Okechukwu P (2024) Modeling geothermal energy potential in the Ruwan-Zafi hot spring region of northeastern Nigeria using high-resolution aeromagnetic data. Model Earth Syst Environ. https://doi.org/10.1007/s40808-024-02023-1

3. Abraham E, Itumoh O, Chukwu C, Rock O (2019) Geothermal Energy Reconnaissance of Southeastern Nigeria from analysis of aeromagnetic and gravity data. Pure Appl Geophys 176:1615–1638. https://doi.org/10.1007/s00024-018-2028-1

4. Amougou OUIO, Mbarga TN, Meying A et al (2020) Interpretation of Aeromagnetic Data to Investigate Crustal structures of the contact Congo Craton-Pan-african Belt at the Eastern Cameroon. Earth Sci Res 9:1–48

5. Bilgin O (2018) The Importance of Geothermal Energy Resources in Turkey. Open Access Libr J 5:1–8. https://doi.org/10.4236/oalib.1104317