A proactive energy-efficient optimal ventilation system using deep learning and AI-iterative dynamic programming under outdoor air quality conditions | ||
---|---|---|
|
||
Ki Jeon Nam†, SungKu Heo†, Qian Li, Jorge Loy-Benitez, MinJeong Kim, DukShin Park, ChangKyoo Yoo*, A proactive energy-efficient optimal ventilation system using deep learning and AI-iterative dynamic programming under outdoor air quality conditions, Applied Energy (ISSN: 0306-2619, SCI, IF=8.5, Top 3% journal – Engineering, Chemical), Elsevier, 266(4), pp.114893 (2020.3) (Ack: 2017R1E1A1A03070713 & Subway Fine Dust: 19QPPW-B152306-01) |
||
이전글 | Energy-efficient time-delay compensated ventilation control system for sustainable subway air quality management under various outdoor conditions | |
다음글 | Feasibility study and performance assessment of a new tri-generation integrated system for power, cooling, and freshwater production |