A proactive energy-efficient optimal ventilation system using artificial intelligent techniques under outdoor air quality conditions-Reference-Cited by-同舟云学术

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A proactive energy-efficient optimal ventilation system using artificial intelligent techniques under outdoor air quality conditions

Published:2020-05 Issue: Volume:266 Page:114893
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Nam KiJeon,Heo SungKu,Li Qian,Loy-Benitez Jorge,Kim MinJeong,Park DuckShin,Yoo ChangKyoo^ORCID

Funder

National Research Foundation

Korea government

Subway Fine Dust Reduction Technology Development Project of the Ministry of Land, Infrastructure, and Transport

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference45 articles.

1. Optimal energy management of urban rail systems: key performance indicators;González-Gil;Energy Convers Manag,2015

2. Estimation of electrical power consumption in subway station design by intelligent approach;Leung;Appl Energy,2013

3. A breakdown of energy consumption in an underground station;Casals;Energy Build,2014

4. Flexible real-time ventilation design in a subway station accommodating the various outdoor PM 10 air quality from climate change variation;Li;Build Environ,2019

5. A systems approach to reduce urban rail energy consumption;González-Gil;Energy Convers Manag,2014

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2. Explainable AI-driven high-fidelity IAQ prediction (HiFi-IAQ) model for subway stations: Spatiotemporal outdoor air quality interpolation using geographic data;Building and Environment;2024-09

3. Energy, thermal comfort, and indoor air quality: Multi-objective optimization review;Renewable and Sustainable Energy Reviews;2024-09

4. A Systematic Review on the Use of AI for Energy Efficiency and Indoor Environmental Quality in Buildings;Sustainability;2024-04-26

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