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Marco Savino Piscitelli ORCID

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  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 (June 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 (December 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 (February 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 (October 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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