[HTML][HTML] Sco** review of post occupancy evaluation of office buildings with focus on indoor environmental quality and productivity
EP Dam-Krogh, RF Rupp, G Clausen… - Journal of Building …, 2024 - Elsevier
Post occupancy evaluation (POE) is used widely to evaluate if a building performs as
envisioned during the design phase, and more importantly, if the occupants feel healthy and …
envisioned during the design phase, and more importantly, if the occupants feel healthy and …
Active Reinforcement Learning for Robust Building Control
Reinforcement learning (RL) is a powerful tool for optimal control that has found great
success in Atari games, the game of Go, robotic control, and building optimization. RL is also …
success in Atari games, the game of Go, robotic control, and building optimization. RL is also …
[HTML][HTML] Prediction of energy efficiency for residential buildings using supervised machine learning algorithms
In the era of digitalization, the large availability of data and innovations in machine learning
algorithms provide new potential to improve the prediction of energy efficiency in buildings …
algorithms provide new potential to improve the prediction of energy efficiency in buildings …
Data-driven Approach to Estimate Urban Heat Island Impacts on Building Energy Consumption
Urban heat island effects can significantly increase building energy consumption. Assessing
the impact of the urban heat island on building energy use is challenging due to temperature …
the impact of the urban heat island on building energy use is challenging due to temperature …
Hybrid Model Predictive Control of Chiller Systems via Collaborative Neurodynamic Optimization
This article addresses the hybrid model predictive control of chiller systems via collaborative
neurodynamic optimization. A mixed-integer optimization problem is formulated for the …
neurodynamic optimization. A mixed-integer optimization problem is formulated for the …
Smart housing: integrating machine learning in sustainable urban planning, interior design, and development
Smart housing, therefore, theoretically becomes very vital in this context of a smart city for
sustainable urban planning and development. Machine learning technologies can be …
sustainable urban planning and development. Machine learning technologies can be …
[HTML][HTML] Energy Consumption Outlier Detection with AI Models in Modern Cities: A Case Study from North-Eastern Mexico
JA Solís-Villarreal, V Soto-Mendoza… - Algorithms, 2024 - mdpi.com
The development of smart cities will require the construction of smart buildings. Smart
buildings will demand the incorporation of elements for efficient monitoring and control of …
buildings will demand the incorporation of elements for efficient monitoring and control of …
[HTML][HTML] Data-driven model predictive control for buildings with glass façade and thermally activated building structure
P Klanatsky, F Veynandt, C Heschl - Energy and Buildings, 2024 - Elsevier
This study presents the development and testing of a Data-driven Model Predictive Control
(DMPC) strategy for optimizing energy efficiency in buildings with glass façades, shading …
(DMPC) strategy for optimizing energy efficiency in buildings with glass façades, shading …
Data-driven characterization of cooling needs in a portfolio of co-located commercial buildings
The increasing cooling needs in commercial buildings, exacerbated by climate change,
warrant immediate attention. These buildings, characterized by their long lifespans and slow …
warrant immediate attention. These buildings, characterized by their long lifespans and slow …
[HTML][HTML] A Scalable and User-Friendly Framework Integrating IoT and Digital Twins for Home Energy Management Systems
The rise in electricity costs for households over the past year has driven significant changes
in energy usage patterns, with many residents adopting smarter energy-efficient practices …
in energy usage patterns, with many residents adopting smarter energy-efficient practices …