Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
[HTML][HTML] Next-generation energy systems for sustainable smart cities: Roles of transfer learning
Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …
improving grid stability and meeting service demand. This is possible by adopting next …
Smart Home Energy Management Systems in Internet of Things networks for green cities demands and services
Today, 44% of global energy has been derived from fossil fuel, which currently poses a
threat to inhabitants and well-being of the environment. In a recent investigation of the global …
threat to inhabitants and well-being of the environment. In a recent investigation of the global …
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings
In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL)
proved to be effective in optimizing the management of integrated energy systems in …
proved to be effective in optimizing the management of integrated energy systems in …
Ten questions concerning reinforcement learning for building energy management
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
[HTML][HTML] Deep reinforcement learning for home energy management system control
The use of machine learning techniques has been proven to be a viable solution for smart
home energy management. These techniques autonomously control heating and domestic …
home energy management. These techniques autonomously control heating and domestic …
[HTML][HTML] Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control
Controlling heating, ventilation and air-conditioning (HVAC) systems is crucial to improving
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
demand-side energy efficiency. At the same time, the thermodynamics of buildings and …
[HTML][HTML] Reinforcement learning building control approach harnessing imitation learning
Reinforcement learning (RL) has shown significant success in sequential decision making in
fields like autonomous vehicles, robotics, marketing and gaming industries. This success …
fields like autonomous vehicles, robotics, marketing and gaming industries. This success …
One for many: Transfer learning for building hvac control
The design of building heating, ventilation, and air conditioning (HVAC) system is critically
important, as it accounts for around half of building energy consumption and directly affects …
important, as it accounts for around half of building energy consumption and directly affects …
Multi-source transfer learning method for enhancing the deployment of deep reinforcement learning in multi-zone building HVAC control
Deep reinforcement learning (DRL) control methods have shown great potential for optimal
HVAC control, but they require significant time and data to learn effective policies. By …
HVAC control, but they require significant time and data to learn effective policies. By …