Development of A Demand Control Algorithm for HVAC Systems to Conserve Energy in Office Buildings
Author:
Affiliation:
1. Skill College of Technology,Department of Civil Engineering,Nugegoda,Sri Lanka
2. Saint Mary’s College,Department of Mathematics & Computer Science,IN,USA
3. SmartAIConnect,Southport,Queensland,Australia,4215
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10406302/10407105/10407435.pdf?arnumber=10407435
Reference27 articles.
1. Energy overview for globalized world economy: Source, supply chain and sink
2. Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
3. A novel deep reinforcement learning based methodology for short-term HVAC system energy consumption prediction
4. A review on buildings energy consumption information
5. Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution
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