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