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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control
Marco Biemann, Fabian Scheller, Xiufeng Liu, et al.
Applied Energy (2021) Vol. 298, pp. 117164-117164
Open Access | Times Cited: 121

Showing 1-25 of 121 citing articles:

Data-driven predictive control for smart HVAC system in IoT-integrated buildings with time-series forecasting and reinforcement learning
Dian Zhuang, Vincent J.L. Gan, Zeynep Duygu Tekler, et al.
Applied Energy (2023) Vol. 338, pp. 120936-120936
Closed Access | Times Cited: 101
Deep reinforcement learning optimal control strategy for temperature setpoint real-time reset in multi-zone building HVAC system
Xi Fang, Guangcai Gong, Guannan Li, et al.
Applied Thermal Engineering (2022) Vol. 212, pp. 118552-118552
Closed Access | Times Cited: 86
Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy
Rendong Shen, Shengyuan Zhong, Xin Wen, et al.
Applied Energy (2022) Vol. 312, pp. 118724-118724
Closed Access | Times Cited: 75
A Systematic Study on Reinforcement Learning Based Applications
Keerthana Sivamayilvelan, R Elakkiya, Belqasem Aljafari, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1512-1512
Open Access | Times Cited: 64
Modelling building HVAC control strategies using a deep reinforcement learning approach
Anh Tuan Nguyen, Duy Hoang Pham, Bee Lan Oo, et al.
Energy and Buildings (2024) Vol. 310, pp. 114065-114065
Closed Access | Times Cited: 30
A comprehensive review of predictive control strategies in heating, ventilation, and air-conditioning (HVAC): Model-free VS model
Xin Xin, Zhihao Zhang, Yong Zhou, et al.
Journal of Building Engineering (2024) Vol. 94, pp. 110013-110013
Closed Access | Times Cited: 24
Successful application of predictive information in deep reinforcement learning control: A case study based on an office building HVAC system
Yuan Gao, Shanrui Shi, Shohei Miyata, et al.
Energy (2024) Vol. 291, pp. 130344-130344
Closed Access | Times Cited: 23
Scalable energy management approach of residential hybrid energy system using multi-agent deep reinforcement learning
Zixuan Wang, Fu Xiao, Ran Yi, et al.
Applied Energy (2024) Vol. 367, pp. 123414-123414
Closed Access | Times Cited: 19
Deep reinforcement learning for PID parameter tuning in greenhouse HVAC system energy Optimization: A TRNSYS-Python cosimulation approach
Misbaudeen Aderemi Adesanya, Hammed Obasekore, Anis Rabiu, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124126-124126
Closed Access | Times Cited: 18
Reinforcement learning for HVAC control in intelligent buildings: A technical and conceptual review
Khalil Al Sayed, Abhinandana Boodi, Roozbeh Sadeghian Broujeny, et al.
Journal of Building Engineering (2024) Vol. 95, pp. 110085-110085
Open Access | Times Cited: 17
Towards optimal HVAC control in non-stationary building environments combining active change detection and deep reinforcement learning
Xiangtian Deng, Yi Zhang, Yi Zhang, et al.
Building and Environment (2022) Vol. 211, pp. 108680-108680
Closed Access | Times Cited: 68
Evaluation of advanced control strategies for building energy systems
Phillip Stoffel, Laura Maier, Alexander Kümpel, et al.
Energy and Buildings (2022) Vol. 280, pp. 112709-112709
Open Access | Times Cited: 60
Energy saving evaluation of an energy efficient data center using a model-free reinforcement learning approach
Muhammad Haiqal Bin Mahbod, Chin Boon Chng, Poh Seng Lee, et al.
Applied Energy (2022) Vol. 322, pp. 119392-119392
Closed Access | Times Cited: 53
Optimal control method of HVAC based on multi-agent deep reinforcement learning
Qiming Fu, Xiyao Chen, Shuai Ma, et al.
Energy and Buildings (2022) Vol. 270, pp. 112284-112284
Closed Access | Times Cited: 52
Real-world implementation and cost of a cloud-based MPC retrofit for HVAC control systems in commercial buildings
Max Bird, Camille Daveau, Edward O’Dwyer, et al.
Energy and Buildings (2022) Vol. 270, pp. 112269-112269
Open Access | Times Cited: 48
Cross temporal-spatial transferability investigation of deep reinforcement learning control strategy in the building HVAC system level
Xi Fang, Guangcai Gong, Guannan Li, et al.
Energy (2022) Vol. 263, pp. 125679-125679
Open Access | Times Cited: 43
Comparative study of model-based and model-free reinforcement learning control performance in HVAC systems
Cheng Gao, Dan Wang
Journal of Building Engineering (2023) Vol. 74, pp. 106852-106852
Closed Access | Times Cited: 40
A comprehensive review of the applications of machine learning for HVAC
Siyang Zhou, A.A. Shah, Puiki Leung, et al.
DeCarbon (2023) Vol. 2, pp. 100023-100023
Open Access | Times Cited: 39
Predictive control optimization of chiller plants based on deep reinforcement learning
Kun He, Qiming Fu, You Lu, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107158-107158
Closed Access | Times Cited: 24
Collaborative optimization of multi-microgrids system with shared energy storage based on multi-agent stochastic game and reinforcement learning
Yijian Wang, Yang Cui, Yang Li, et al.
Energy (2023) Vol. 280, pp. 128182-128182
Open Access | Times Cited: 22
Enhancing HVAC control systems through transfer learning with deep reinforcement learning agents
Kevlyn Kadamala, Des Chambers, Enda Barrett
Smart Energy (2024) Vol. 13, pp. 100131-100131
Open Access | Times Cited: 15
Artificial Neural Network Applications for Energy Management in Buildings: Current Trends and Future Directions
Panagiotis Michailidis, Iakovos Michailidis, Socratis Gkelios, et al.
Energies (2024) Vol. 17, Iss. 3, pp. 570-570
Open Access | Times Cited: 9
Towards various occupants with different thermal comfort requirements: A deep reinforcement learning approach combined with a dynamic PMV model for HVAC control in buildings
Zekun Shi, Ruifan Zheng, Jun Zhao, et al.
Energy Conversion and Management (2024) Vol. 320, pp. 118995-118995
Closed Access | Times Cited: 8
HVAC Control Based on Reinforcement Learning and Fuzzy Reasoning: Optimizing HVAC Supply Air Temperature, Flow Rate, and Velocity
Leehter Yao, L Huang, J. C. Teo
Journal of Building Engineering (2025) Vol. 103, pp. 112143-112143
Closed Access | Times Cited: 1
Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings
Raad Z. Homod, Hussein Togun, Ahmed Kadhim Hussein, et al.
Applied Energy (2022) Vol. 313, pp. 118863-118863
Closed Access | Times Cited: 36
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