Using machine learning to expound energy poverty in the global south: Understanding and predicting access to cooking with clean energy-Reference-Cited by-同舟云学术

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Using machine learning to expound energy poverty in the global south: Understanding and predicting access to cooking with clean energy

Published:2023-10 Issue: Volume:14 Page:100290
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Mukelabai M.D.^ORCID,Wijayantha K.G.U.,Blanchard R.E.

Funder

Engineering and Physical Sciences Research Council

Loughborough University

UK Research and Innovation

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Energy,Engineering (miscellaneous)

Reference79 articles.

1. UN. The sustainable development goals report. New York, NY, USA: 2022.

2. Access to clean cooking services in energy and emission scenarios after COVID-19;Pachauri;Nat Energy,2021

3. The state of access to modern energy cooking services (English),2020

4. Household cooking fuel estimates at global and country level for 1990 to 2030;Stoner;Nat Commun,2021

5. WHO. Household air pollution - Fact Sheets 2022. 10.1093/med/9780199929573.003.0023.

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1. Risk assessment of unclean cooking energy usage from the perspective of subjective wellbeing: The mediating role of perceived physical and mental health;Ecotoxicology and Environmental Safety;2024-08

2. Energy poverty prediction in the United Kingdom: A machine learning approach;Energy Policy;2024-01

3. Addressing Challenges in Delivering Sustainable Rural Water Provision Using Solar Water Pumping in Malawi: A Stakeholder Analysis;Energies;2023-11-24

4. Application of machine learning to assess people's perception of household energy in the developing world: A case of Nepal;Energy and AI;2023-10

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