Spatial analysis and predictive modeling of energy poverty: insights for policy implementation
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10668-024-05015-4.pdf
Reference157 articles.
1. Abbas, K., Li, S., Xu, D., Baz, K., & Rakhmetova, A. (2020). Do socioeconomic factors determine household multidimensional energy poverty? Empirical evidence from South Asia. Energy Policy, 146, 111754. https://doi.org/10.1016/j.enpol.2020.111754
2. Acharya, R. H., & Sadath, A. C. (2019). Energy poverty and economic development: Household-level evidence from India. Energy and Buildings, 183, 785–791. https://doi.org/10.1016/j.enbuild.2018.11.047
3. Adnan, M., AlSaeed, D. H., Al-Baity, H. H., & Rehman, A. (2021). Leveraging the power of deep learning technique for creating an intelligent, context-aware, and adaptive M-learning model. Complexity, 2021, 1–21. https://doi.org/10.1155/2021/5519769
4. Agbo, K. E., Walgraeve, C., Eze, J. I., Ugwoke, P. E., Ukoha, P. O., & Van Langenhove, H. (2021). A review on ambient and indoor air pollution status in Africa. Atmospheric Pollution Research, 12, 243–260. https://doi.org/10.1016/j.apr.2020.11.006
5. Ahmad, M. W., Mourshed, M., & Rezgui, Y. (2017). Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption. Energy and Buildings, 147, 77–89. https://doi.org/10.1016/j.enbuild.2017.04.038
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