BRANDI, SILVIO

BRANDI, SILVIO  

Dipartimento Energia  

041274  

Mostra records
Risultati 1 - 15 di 15 (tempo di esecuzione: 0.034 secondi).
Citazione Data di pubblicazione Autori File
Mining typical load profiles in buildings to support energy management in the smart city context / Capozzoli, Alfonso; Piscitelli, Marco Savino; Brandi, Silvio. - In: ENERGY PROCEDIA. - ISSN 1876-6102. - 134:(2017), pp. 865-874. [10.1016/j.egypro.2017.09.545] 1-gen-2017 Capozzoli, AlfonsoPiscitelli, Marco SavinoBRANDI, SILVIO 1-s2.0-S187661021734674X-main.pdf
Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings / Capozzoli, Alfonso; Piscitelli, Marco Savino; Brandi, Silvio; Grassi, Daniele; Chicco, Gianfranco. - In: ENERGY. - ISSN 0360-5442. - STAMPA. - 157:(2018), pp. 336-352. [10.1016/j.energy.2018.05.127] 1-gen-2018 Capozzoli, AlfonsoPiscitelli, Marco SavinoBrandi, SilvioGrassi, DanieleChicco, Gianfranco -
Recognition and classification of typical load profiles in buildings with non-intrusive learning approach / Piscitelli, M. S.; Brandi, S.; Capozzoli, A.. - In: APPLIED ENERGY. - ISSN 0306-2619. - 255:(2019). [10.1016/j.apenergy.2019.113727] 1-gen-2019 Piscitelli M. S.Brandi S.Capozzoli A. 1-s2.0-S030626191931414X-main.pdfManuscript_with no changes marked .pdf
Advanced Control Strategies For The Modulation of Solar Radiation In Buildings: MPC-enhanced Rule-based Control / Piscitelli, MARCO SAVINO; Brandi, Silvio; Gennaro, Giovanni; Capozzoli, Alfonso; Favoino, Fabio; Serra, Valentina. - STAMPA. - 16:(2020). (Intervento presentato al convegno International Building Performance Simulation Conference tenutosi a Roma nel September 2019). 1-gen-2020 Marco Savino PiscitelliSilvio BrandiGiovanni GennaroAlfonso CapozzoliFabio FavoinoValentina Serra -
Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings / Brandi, S.; Piscitelli, M. S.; Martellacci, M.; Capozzoli, A.. - In: ENERGY AND BUILDINGS. - ISSN 0378-7788. - 224:(2020), p. 110225. [10.1016/j.enbuild.2020.110225] 1-gen-2020 Brandi S.Piscitelli M. S.Capozzoli A. + brandi 2020.pdfdeep reinforcement learning.pdf
A data analytics-based tool for the detection and diagnosis of anomalous daily energy patterns in buildings / Piscitelli, M. S.; Brandi, S.; Capozzoli, A.; Xiao, F.. - In: BUILDING SIMULATION. - ISSN 1996-3599. - (2020). [10.1007/s12273-020-0650-1] 1-gen-2020 Piscitelli M. S.Brandi S.Capozzoli A. + Piscitelli 2020.pdfA data analytics based tool.pdf
Online implementation of a soft actor-critic agent to enhance indoor temperature control and energy efficiency in buildings / Coraci, D.; Brandi, S.; Piscitelli, M. S.; Capozzoli, A.. - In: ENERGIES. - ISSN 1996-1073. - 14:4(2021), p. 997. [10.3390/en14040997] 1-gen-2021 Coraci D.Brandi S.Piscitelli M. S.Capozzoli A. energies-14-00997-v2.pdf
A predictive and adaptive control strategy to optimize the management of integrated energy systems in buildings / Brandi, S.; Gallo, A.; Capozzoli, A.. - In: ENERGY REPORTS. - ISSN 2352-4847. - 8:(2022), pp. 1550-1567. [10.1016/j.egyr.2021.12.058] 1-gen-2022 Brandi S.Gallo A.Capozzoli A. 1-s2.0-S2352484721014979.pdf
Energy Management of a Residential Heating System Through Deep Reinforcement Learning / Brandi, S.; Coraci, D.; Borello, D.; Capozzoli, A.. - STAMPA. - 263:(2022), pp. 329-339. (Intervento presentato al convegno 13th KES International Conference on Sustainability and Energy in Buildings, SEB 2021 nel 2021) [10.1007/978-981-16-6269-0_28]. 1-gen-2022 Brandi S.Coraci D.Capozzoli A. + Energy Management of a Residential Heating System Through Deep Reinforcement Learning.pdf
Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management / Brandi, S.; Fiorentini, M.; Capozzoli, A.. - In: AUTOMATION IN CONSTRUCTION. - ISSN 0926-5805. - ELETTRONICO. - 135:(2022), p. 104128. [10.1016/j.autcon.2022.104128] 1-gen-2022 Brandi S.Fiorentini M.Capozzoli A. 1-s2.0-S0926580522000012-main.pdf
Deep Reinforcement Learning-based Control Strategies for Enhancing Energy Management in HVAC Systems / Brandi, Silvio. - (2022 Jul 07), pp. 1-220. 7-lug-2022 BRANDI, SILVIO PhD_Thesis_Brandi.pdfPhD_Thesis_Brandi_Abstract.pdf
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings / Coraci, Davide; Brandi, Silvio; Hong, Tianzhen; Capozzoli, Alfonso. - In: APPLIED ENERGY. - ISSN 0306-2619. - STAMPA. - 333:(2023), p. 120598. [10.1016/j.apenergy.2022.120598] 1-gen-2023 Davide CoraciSilvio BrandiAlfonso Capozzoli + 1-s2.0-S0306261922018554-main.pdfOnline transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings.pdf
Effective pre-training of a deep reinforcement learning agent by means of long short-term memory models for thermal energy management in buildings / Coraci, D.; Brandi, S.; Capozzoli, A.. - In: ENERGY CONVERSION AND MANAGEMENT. - ISSN 0196-8904. - STAMPA. - 291:(2023). [10.1016/j.enconman.2023.117303] 1-gen-2023 Coraci D.Brandi S.Capozzoli A. Capozzoli-Effective.pdf
Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control / Silvestri, Alberto; Coraci, Davide; Brandi, Silvio; Capozzoli, Alfonso; Borkowski, Esther; Köhler, Johannes; Wu, Duan; Zeilinger, Melanie N.; Schlueter, Arno. - In: APPLIED ENERGY. - ISSN 0306-2619. - 368:(2024). [10.1016/j.apenergy.2024.123447] 1-gen-2024 Davide CoraciSilvio BrandiAlfonso Capozzoli + Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control.pdf
An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems / Coraci, Davide; Brandi, Silvio; Hong, Tianzhen; Capozzoli, Alfonso. - In: BUILDING SIMULATION. - ISSN 1996-3599. - (2024). [10.1007/s12273-024-1109-6] 1-gen-2024 Coraci, DavideBrandi, SilvioCapozzoli, Alfonso + An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems.pdf