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Marco Savino Piscitelli ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Chiosa, Roberto / Piscitelli, Marco Savino / Pritoni, Marco / Capozzoli, Alfonso (2024): A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema. In: Energy and Buildings, v. 323 (November 2024).

    https://doi.org/10.1016/j.enbuild.2024.114802

  2. Fan, Cheng / Lin, Yiwen / Piscitelli, Marco Savino / Chiosa, Roberto / Wang, Huilong / Capozzoli, Alfonso / Ma, Yuanyuan (2023): Leveraging graph convolutional networks for semi-supervised fault diagnosis of HVAC systems in data-scarce contexts. In: Building Simulation, v. 16, n. 8 (Juni 2023).

    https://doi.org/10.1007/s12273-023-1041-1

  3. Pinto, Giuseppe / Messina, Riccardo / Li, Han / Hong, Tianzhen / Piscitelli, Marco Savino / Capozzoli, Alfonso (2022): Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics. In: Energy and Buildings, v. 276 (Dezember 2022).

    https://doi.org/10.1016/j.enbuild.2022.112530

  4. Chiosa, Roberto / Piscitelli, Marco Savino / Fan, Cheng / Capozzoli, Alfonso (2022): Towards a self-tuned data analytics-based process for an automatic context-aware detection and diagnosis of anomalies in building energy consumption timeseries. In: Energy and Buildings, v. 270 (September 2022).

    https://doi.org/10.1016/j.enbuild.2022.112302

  5. Capozzoli, Alfonso / Piscitelli, Marco Savino / Gorrino, Alice / Ballarini, Ilaria / Corrado, Vincenzo (2017): Data analytics for occupancy pattern learning to reduce the energy consumption of HVAC systems in office buildings. In: Sustainable Cities and Society, v. 35 (November 2017).

    https://doi.org/10.1016/j.scs.2017.07.016

  6. Piscitelli, Marco Savino / Brandi, Silvio / Capozzoli, Alfonso / Xiao, Fu (2020): A data analytics-based tool for the detection and diagnosis of anomalous daily energy patterns in buildings. In: Building Simulation, v. 14, n. 1 (November 2020).

    https://doi.org/10.1007/s12273-020-0650-1

  7. Capozzoli, Alfonso / Serale, Gianluca / Piscitelli, Marco Savino / Grassi, Daniele (2017): Data mining for energy analysis of a large data set of flats. In: Proceedings of the Institution of Civil Engineers - Engineering Sustainability, v. 170, n. 1 (Februar 2017).

    https://doi.org/10.1680/jensu.15.00051

  8. Brandi, Silvio / Piscitelli, Marco Savino / Martellacci, Marco / Capozzoli, Alfonso (2020): Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings. In: Energy and Buildings, v. 224 (Oktober 2020).

    https://doi.org/10.1016/j.enbuild.2020.110225

  9. Piscitelli, Marco Savino / Mazzarelli, Daniele Mauro / Capozzoli, Alfonso (2020): Enhancing operational performance of AHUs through an advanced fault detection and diagnosis process based on temporal association and decision rules. In: Energy and Buildings, v. 226 (November 2020).

    https://doi.org/10.1016/j.enbuild.2020.110369

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