Predicting climate-driven changes in reservoir inflows and hydropower in Côte d'Ivoire using machine learning modeling-Reference-Cited by-同舟云学术

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Predicting climate-driven changes in reservoir inflows and hydropower in Côte d'Ivoire using machine learning modeling

Published:2024-09 Issue: Volume:302 Page:131849
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Obahoundje Salomon^ORCID,Diedhiou Arona^ORCID,Akpoti Komlavi^ORCID,Kouassi Kouakou Lazare,Ofosu Eric Antwi,Marcel Kouame Didier Guy

Funder

Agence nationale de la recherche

French National Research Institute for Sustainable Development

Publisher

Elsevier BV

Reference57 articles.

1. Technological advances in prospecting sites for pumped hydro energy storage;Akpoti,2023

2. IHA. Hydropower Status Report 2022. https://www.hydropower.org/publications/2022-hydropower-status-report.

3. Africa energy review 2021,2021

4. Hydropower status report 2020,2020

5. The role of hydropower in climate change mitigation and adaptation: a review;Berga;Engineering,2016

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evaluating machine learning models in predicting dam inflow and hydroelectric power production in multi-purpose dams (case study: Mahabad Dam, Iran);Applied Water Science;2024-08-20

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