Comparative Analysis of Energy Poverty Prediction Models Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Comparative Analysis of Energy Poverty Prediction Models Using Machine Learning Algorithms

Published:2021-10-31 Issue:5 Volume:56 Page:239-255
ISSN:1226-7147
Container-title:Journal of Korea Planning Association
language:en
Short-container-title:jkpa

Author:

Hong Zhe,Park In Kwon

Funder

Ministry of Education

National Research Foundation of Korea

Publisher

Korea Planners Association

Cited by 5 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. Evolving energy landscapes: A computational analysis of the determinants of energy poverty;Renewable and Sustainable Energy Reviews;2024-09

2. Artificial Neural Networks as a Tool to Understand Complex Energy Poverty Relationships: The Case of Greece;Energies;2024-06-27

3. Predictive Modeling of Energy Poverty with Machine Learning Ensembles: Strategic Insights from Socioeconomic Determinants for Effective Policy Implementation;International Journal of Energy Research;2024-01

4. Evolving Energy Landscapes: a Computational Analysis of the Determinants of Energy Poverty;2024

5. Predictive Modeling of Energy Poverty with Machine Learning Ensembles: Strategic Insights from Socio-Economic Determinants for Effective Policy Implementation;2024

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