Mohammad Esrafilian-Najafabadi
- Transfer learning for occupancy-based HVAC control: A data-driven approach using unsupervised learning of occupancy profiles and deep reinforcement learning. Dans: Energy and Buildings, v. 300 (décembre 2023). (2023):
- Towards self-learning control of HVAC systems with the consideration of dynamic occupancy patterns: Application of model-free deep reinforcement learning. Dans: Building and Environment, v. 226 (décembre 2022). (2022):
- Impact of predictor variables on the performance of future occupancy prediction: Feature selection using genetic algorithms and machine learning. Dans: Building and Environment, v. 219 (juillet 2022). (2022):
- Impact of occupancy prediction models on building HVAC control system performance: Application of machine learning techniques. Dans: Energy and Buildings, v. 257 (février 2022). (2022):
- Occupancy-based HVAC control using deep learning algorithms for estimating online preconditioning time in residential buildings. Dans: Energy and Buildings, v. 252 (décembre 2021). (2021):
- Occupancy-based HVAC control systems in buildings: A state-of-the-art review. Dans: Building and Environment, v. 197 (juin 2021). (2021):