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Forecasting coal power plant retirement ages and lock-in with random forest regression
Averting dangerous climate change requires expediting the retirement of coal-fired power plants (CFPPs). Given multiple barriers hampering this, here we forecast the future retirement ages of the world’s CFPPs. We use supervised machine learning to first learn from the past, determining the factors...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382988/ https://www.ncbi.nlm.nih.gov/pubmed/37521043 http://dx.doi.org/10.1016/j.patter.2023.100776 |