Artificial Neural Networks as a Tool to Understand Complex Energy Poverty Relationships: The Case of Greece
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Cited by:
- Takako Mochida & Andrew Chapman & Benjamin Craig McLellan, 2025. "Exploring Energy Poverty: Toward a Comprehensive Predictive Framework," Energies, MDPI, vol. 18(10), pages 1-23, May.
- Elpida Kalfountzou & Lefkothea Papada & Christos Tourkolias & Sevastianos Mirasgedis & Dimitris Kaliampakos & Dimitris Damigos, 2025. "A Comparative Analysis of Machine Learning Algorithms in Energy Poverty Prediction," Energies, MDPI, vol. 18(5), pages 1-20, February.
- Urszula Grzybowska & Agnieszka Wojewódzka-Wiewiórska & Gintarė Vaznonienė & Hanna Dudek, 2024. "Households Vulnerable to Energy Poverty in the Visegrad Group Countries: An Analysis of Socio-Economic Factors Using a Machine Learning Approach," Energies, MDPI, vol. 17(24), pages 1-23, December.
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