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:

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

Showing 1-25 of 52 citing articles:

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: 62

ED-DQN: An event-driven deep reinforcement learning control method for multi-zone residential buildings
Qiming Fu, Li Zhu, Zhengkai Ding, et al.
Building and Environment (2023) Vol. 242, pp. 110546-110546
Closed Access | Times Cited: 49

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: 17

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: 37

An occupant-centric control strategy for indoor thermal comfort, air quality and energy management
Zu Wang, John Kaiser Calautit, Paige Wenbin Tien, et al.
Energy and Buildings (2023) Vol. 285, pp. 112899-112899
Closed Access | Times Cited: 30

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

Energy optimization for HVAC systems in multi-VAV open offices: A deep reinforcement learning approach
Hao Wang, Xiwen Chen, Natan Vital, et al.
Applied Energy (2023) Vol. 356, pp. 122354-122354
Open Access | Times Cited: 20

An experimental evaluation of deep reinforcement learning algorithms for HVAC control
Antonio Manjavacas, Alejandro Campoy-Nieves, Javier Jiménez-Raboso, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 7
Open Access | Times Cited: 5

An environment-adaptive SAC-based HVAC control of single-zone residential and office buildings
Xinlin Wang, Nariman Mahdavi, Subbu Sethuvenkatraman, et al.
Data-Centric Engineering (2025) Vol. 6
Open Access

A novel energy saving framework based on optimal chiller loading and parameter optimization for HVAC: a case study for subway station
Yuanyang Hu, Luwen Qin, Shuhong Li, et al.
Journal of Building Engineering (2025), pp. 111887-111887
Closed Access

Energy-efficient control of thermal comfort in multi-zone residential HVAC via reinforcement learning
Zhengkai Ding, Qiming Fu, Jianping Chen, et al.
Connection Science (2022) Vol. 34, Iss. 1, pp. 2364-2394
Open Access | Times Cited: 24

A laboratory test of an Offline-trained Multi-Agent Reinforcement Learning Algorithm for Heating Systems
Christian Blad, Simon Bøgh, Carsten Skovmose Kallesøe, et al.
Applied Energy (2023) Vol. 337, pp. 120807-120807
Open Access | Times Cited: 14

Dynamic indoor thermal environment using Reinforcement Learning-based controls: Opportunities and challenges
Arnab Chatterjee, Dolaana Khovalyg
Building and Environment (2023) Vol. 244, pp. 110766-110766
Open Access | Times Cited: 14

Advancing Sustainable Building Practices: Intelligent Methods for Enhancing Heating and Cooling Energy Efficiency
Abdelali Agouzoul, Emmanuel Simeu, Mohamed Tabaa
Sustainability (2024) Vol. 16, Iss. 7, pp. 2879-2879
Open Access | Times Cited: 4

Energy management based on safe multi-agent reinforcement learning for smart buildings in distribution networks
Yiyun Sun, Senlin Zhang, Meiqin Liu, et al.
Energy and Buildings (2024) Vol. 318, pp. 114410-114410
Closed Access | Times Cited: 4

HVAC control in buildings using neural network
A. Abida, Pascal Richter
Journal of Building Engineering (2022) Vol. 65, pp. 105558-105558
Closed Access | Times Cited: 21

Systematic Review on Deep Reinforcement Learning-Based Energy Management for Different Building Types
Ayas Shaqour, Aya Hagishima
Energies (2022) Vol. 15, Iss. 22, pp. 8663-8663
Open Access | Times Cited: 20

ANN-based procedure to obtain the optimal design and operation of the compression chiller network – Energy, economic and environmental analysis
Navid Moghaddas-Zadeh, Mahmood Farzaneh-Gord, Amir Ebrahimi‐Moghadam, et al.
Journal of Building Engineering (2023) Vol. 72, pp. 106711-106711
Closed Access | Times Cited: 10

Efficient model-free control of chiller plants via cluster-based deep reinforcement learning
Kun He, Qiming Fu, You Lu, et al.
Journal of Building Engineering (2023) Vol. 82, pp. 108345-108345
Closed Access | Times Cited: 10

A Sustainability Evaluation of Buildings: A Review on Sustainability Factors to Move towards a Greener City Environment
Lee Won Park, Keonhee Cho, Myeong-in Choi
Buildings (2024) Vol. 14, Iss. 2, pp. 446-446
Open Access | Times Cited: 3

Hybrid model-free control based on deep reinforcement learning: An energy-efficient operation strategy for HVAC systems
Xiaoming Zhang, Xinwei Wang, Haotian Zhang, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110410-110410
Closed Access | Times Cited: 3

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