Jayson Bursill
- Deployment of real-time building automation system-integrated inverse-model-based fault detection and diagnostics algorithms. In: Science and Technology for the Built Environment, v. 30, n. 2 (Januar 2024). (2024):
- Estimating energy savings from HVAC controls fault correction through inverse greybox model-based virtual metering. In: Energy and Buildings, v. 282 (März 2023). (2023):
- Inverse model-based detection of programming logic faults in multiple zone VAV AHU systems. In: Building and Environment, v. 211 (März 2022). (2022):
- The in-situ implementation of a feature-rich thermostat: A building engineering and human factors approach to improve perceived control in offices. In: Building and Environment, v. 199 (Juli 2021). (2021):
- Experimental application of classification learning to generate simplified model predictive controls for a shared office heating system. In: Science and Technology for the Built Environment, v. 25, n. 5 (28 Mai 2019). (2019):
- Development and implementation of a thermostat learning algorithm. In: Science and Technology for the Built Environment, v. 24, n. 1 (Oktober 2017). (2017):
- Multi-zone field study of rule extraction control to simplify implementation of predictive control to reduce building energy use. In: Energy and Buildings, v. 222 (September 2020). (2020):
- Disaggregation of commercial building end-uses with automation system data. In: Energy and Buildings, v. 223 (September 2020). (2020):
- Proxy zone-level energy use estimation in a commercial building with a variable air volume system. In: Journal of Building Engineering, v. 33 (Januar 2021). (2021):
- Shortest-prediction-horizon model-based predictive control for individual offices. In: Building and Environment, v. 82 (Dezember 2014). (2014):