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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:

Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning
Yan Du, Helia Zandi, Olivera Kotevska, et al.
Applied Energy (2020) Vol. 281, pp. 116117-116117
Open Access | Times Cited: 188

Showing 1-25 of 188 citing articles:

Strategies to save energy in the context of the energy crisis: a review
Mohamed Farghali, Ahmed I. Osman, Israa M. A. Mohamed, et al.
Environmental Chemistry Letters (2023) Vol. 21, Iss. 4, pp. 2003-2039
Open Access | Times Cited: 262
An overview of machine learning applications for smart buildings
Kari Alanne, Seppo Sierla
Sustainable Cities and Society (2021) Vol. 76, pp. 103445-103445
Open Access | Times Cited: 191
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: 118
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
Safe reinforcement learning for real-time automatic control in a smart energy-hub
Dawei Qiu, Zihang Dong, Xi Zhang, et al.
Applied Energy (2022) Vol. 309, pp. 118403-118403
Closed Access | Times Cited: 81
Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids
Maryam Saleem, Mustafa Shakir, Muhammad Rehan Usman, et al.
Energies (2023) Vol. 16, Iss. 12, pp. 4835-4835
Open Access | Times Cited: 66
Comparison of reinforcement learning and model predictive control for building energy system optimization
Dan Wang, Wanfu Zheng, Zhe Wang, et al.
Applied Thermal Engineering (2023) Vol. 228, pp. 120430-120430
Closed Access | Times Cited: 58
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings
Davide Coraci, Silvio Brandi, Tianzhen Hong, et al.
Applied Energy (2023) Vol. 333, pp. 120598-120598
Open Access | Times Cited: 53
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: 52
Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Yasaman Balali, Adrian Chong, Andrew Busch, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 183, pp. 113496-113496
Open Access | Times Cited: 51
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
Occupant-centric HVAC and window control: A reinforcement learning model for enhancing indoor thermal comfort and energy efficiency
X. Liu, Zhonghua Gou
Building and Environment (2024) Vol. 250, pp. 111197-111197
Closed Access | Times Cited: 26
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: 23
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: 22
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
Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control
Alberto Silvestri, Davide Coraci, Silvio Brandi, et al.
Applied Energy (2024) Vol. 368, pp. 123447-123447
Open Access | Times Cited: 15
Multi-agent deep reinforcement learning based HVAC control for multi-zone buildings considering zone-energy-allocation optimization
Wenping Xue, Ning Jia, Ming Zhao
Energy and Buildings (2025) Vol. 329, pp. 115241-115241
Closed Access | Times Cited: 3
Privacy Preserving Load Control of Residential Microgrid via Deep Reinforcement Learning
Zhaoming Qin, Di Liu, Haochen Hua, et al.
IEEE Transactions on Smart Grid (2021) Vol. 12, Iss. 5, pp. 4079-4089
Closed Access | Times Cited: 78
Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management
Silvio Brandi, Massimo Fiorentini, Alfonso Capozzoli
Automation in Construction (2022) Vol. 135, pp. 104128-104128
Open Access | Times Cited: 64
A data-driven strategy using long short term memory models and reinforcement learning to predict building electricity consumption
Xinlei Zhou, Wenye Lin, Ritunesh Kumar, et al.
Applied Energy (2021) Vol. 306, pp. 118078-118078
Closed Access | Times Cited: 57
A new multi-data-driven spatiotemporal PM2.5 forecasting model based on an ensemble graph reinforcement learning convolutional network
Xinwei Liu, Muchuan Qin, Yue He, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 10, pp. 101197-101197
Closed Access | Times Cited: 56
A systematic review of machine learning techniques related to local energy communities
Alejandro Hernandez-Matheus, Markus Löschenbrand, Kjersti Berg, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 170, pp. 112651-112651
Open Access | Times Cited: 56
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
Energy-efficient personalized thermal comfort control in office buildings based on multi-agent deep reinforcement learning
Liang Yu, Zhanbo Xu, Tengfei Zhang, et al.
Building and Environment (2022) Vol. 223, pp. 109458-109458
Closed Access | Times Cited: 48
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