Model free optimization of building cooling water systems with refined action space
Author:
Publisher
Springer Science and Business Media LLC
Subject
Energy (miscellaneous),Building and Construction
Link
https://link.springer.com/content/pdf/10.1007/s12273-022-0956-2.pdf
Reference25 articles.
1. Ahn KU, Park CS (2020). Application of deep Q-networks for model-free optimal control balancing between different HVAC systems. Science and Technology for the Built Environment, 26: 61–74.
2. Biemann M, Scheller F, Liu X, et al. (2021). Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control. Applied Energy, 298: 117164.
3. Du Y, Li F, Munk J, et al. (2021a). Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control. Electric Power Systems Research, 192: 106959.
4. Du Y, Zandi H, Kotevska O, et al. (2021b). Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning. Applied Energy, 281: 116117.
5. Friedman JH (2001) Greedy function approximation: A gradient boosting machine. The Annals of Statistics, 29: 1189–1232.
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Active learning concerning sampling cost for enhancing AI-enabled building energy system modeling;Advances in Applied Energy;2024-12
2. Energy modeling and optimization of building condenser water systems with all-variable speed pumps and tower fans: A case study;Building Simulation;2024-06-20
3. Efficient model-free control of chiller plants via cluster-based deep reinforcement learning;Journal of Building Engineering;2024-04
4. An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems;Building Simulation;2024-02-20
5. Deep Reinforcement Learning Based HVAC Optimization Control Algorithm Application;2023 IEEE International Conference on Electrical, Automation and Computer Engineering (ICEACE);2023-12-29
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3