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Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset
2022 Li, H.; Pinto, G.; Capozzoli, A.; Hong, T.
The impact of stakeholder preferences in multicriteria evaluation for the retrofitting of office buildings in Italy
2020 Pinto, G.; Capozzoli, A.; Piscitelli, M. S.; Savoldi, L.
Citazione | Data di pubblicazione | Autori | File |
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Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset / Li, H.; Pinto, G.; Capozzoli, A.; Hong, T.. - ELETTRONICO. - (2022), pp. 242-245. (Intervento presentato al convegno BuildSys '22: The 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation tenutosi a Boston (USA) nel 9 - 10 Novembre, 2022) [10.1145/3563357.3564056]. | 1-gen-2022 | Pinto G.Capozzoli A. + | 3563357.3564056.pdf |
The impact of stakeholder preferences in multicriteria evaluation for the retrofitting of office buildings in Italy / Pinto, G.; Capozzoli, A.; Piscitelli, M. S.; Savoldi, L.. - STAMPA. - 163:(2020), pp. 581-591. (Intervento presentato al convegno 11th International Conference on Sustainability and Energy in Buildings, SEB 2019 tenutosi a Budapest (HUN) nel 4th -5th July 2019) [10.1007/978-981-32-9868-2_49]. | 1-gen-2020 | Pinto G.Capozzoli A.Piscitelli M. S.Savoldi L. | The impact of stakeholder preferences in multicriteria evaluation for the retrofitting of office buildings in Italy.pdf |