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Roberto Chiosa
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A review of data-driven fault detection and diagnostics for building HVAC systems
Z Chen, Z O’Neill, J Wen, O Pradhan, T Yang, X Lu, G Lin, S Miyata, S Lee, ...
Applied Energy 339, 121030, 2023
412023
Data-centric or algorithm-centric: Exploiting the performance of transfer learning for improving building energy predictions in data-scarce context
C Fan, Y Lei, Y Sun, MS Piscitelli, R Chiosa, A Capozzoli
Energy 240, 122775, 2022
322022
A data analytics-based energy information system (eis) tool to perform meter-level anomaly detection and diagnosis in buildings
R Chiosa, MS Piscitelli, A Capozzoli
Energies 14 (1), 237, 2021
282021
Towards a self-tuned data analytics-based process for an automatic context-aware detection and diagnosis of anomalies in building energy consumption timeseries
R Chiosa, MS Piscitelli, C Fan, A Capozzoli
Energy and Buildings 270, 112302, 2022
82022
Leveraging graph convolutional networks for semi-supervised fault diagnosis of HVAC systems in data-scarce contexts
C Fan, Y Lin, MS Piscitelli, R Chiosa, H Wang, A Capozzoli, Y Ma
Building Simulation 16 (8), 1499-1517, 2023
42023
Application of data analytics processes for the detection of anomalous energy patterns in buildings
S Deho
Politecnico di Torino, 2021
2021
Detection and diagnosis of anomalous energy consumption patterns in buildings through a data analytics based approach: the case of Politecnico di Torino
R Chiosa
Politecnico di Torino, 2020
2020
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