Alfonso Capozzoli
- An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems. In: Building Simulation, v. 17, n. 5 (Januar 2024). (2024):
- 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). (2023):
- Ten questions concerning reinforcement learning for building energy management. In: Building and Environment, v. 241 (August 2023). (2023):
- Experimental assessment of ground-truth faults in a typical single-duct dual-fan air-handling unit under Mediterranean climatic conditions: Impact scenarios of sensors’ offset and fans’ failure. In: Energy and Buildings, v. 275 (November 2022). (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). (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). (2022):
- Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management. In: Automation in Construction, v. 135 (März 2022). (2022):
- Enhancing energy efficiency and comfort in buildings through model predictive control for dynamic façades with electrochromic glazing. In: Journal of Building Engineering, v. 43 (November 2021). (2021):
- 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). (2017):
- 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). (2020):
- 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). (2017):
- Thermal bridges in vacuum insulation panels at building scale. In: Proceedings of the Institution of Civil Engineers - Engineering Sustainability, v. 170, n. 1 (Februar 2017). (2017):
- Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings. In: Energy and Buildings, v. 224 (Oktober 2020). (2020):
- Estimation models of heating energy consumption in schools for local authorities planning. In: Energy and Buildings, v. 105 (Oktober 2015). (2015):
- Experimental and numerical investigation of thermal bridging effects of jointed Vacuum Insulation Panels. In: Energy and Buildings, v. 111 (Januar 2016). (2016):
- 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). (2020):
- Development and evaluation of a comfort-oriented control strategy for thermal management of mixed-mode ventilated buildings. In: Energy and Buildings, v. 202 (November 2019). (2019):
- Analysis of the temperature dependence of the thermal conductivity in Vacuum Insulation Panels. In: Energy and Buildings, v. 183 (Januar 2019). (2019):