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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:

A review of machine learning in building load prediction
Liang Zhang, Jin Wen, Yanfei Li, et al.
Applied Energy (2021) Vol. 285, pp. 116452-116452
Open Access | Times Cited: 447

Showing 1-25 of 447 citing articles:

Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm
Tanveer Ahmad, Rafał Madoński, Dongdong Zhang, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 160, pp. 112128-112128
Closed Access | Times Cited: 352
AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
Yassine Himeur, Mariam Elnour, Fodil Fadli, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 4929-5021
Open Access | Times Cited: 272
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Giuseppe Pinto, Zhe Wang, Abhishek Roy, et al.
Advances in Applied Energy (2022) Vol. 5, pp. 100084-100084
Open Access | Times Cited: 188
Review and prospect of data-driven techniques for load forecasting in integrated energy systems
Jizhong Zhu, Hanjiang Dong, Weiye Zheng, et al.
Applied Energy (2022) Vol. 321, pp. 119269-119269
Closed Access | Times Cited: 174
Interpretable machine learning for building energy management: A state-of-the-art review
Zhe Chen, Fu Xiao, Fangzhou Guo, et al.
Advances in Applied Energy (2023) Vol. 9, pp. 100123-100123
Open Access | Times Cited: 161
Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption — A systematic review
Mohamad Khalil, A. Stephen McGough, Zoya Pourmirza, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105287-105287
Closed Access | Times Cited: 154
Building energy prediction using artificial neural networks: A literature survey
Chujie Lu, Sihui Li, Zhengjun Lu
Energy and Buildings (2021) Vol. 262, pp. 111718-111718
Closed Access | Times Cited: 148
A review of data-driven fault detection and diagnostics for building HVAC systems
Zhelun Chen, Zheng O’Neill, Jin Wen, et al.
Applied Energy (2023) Vol. 339, pp. 121030-121030
Open Access | Times Cited: 116
Integrity assessment of corroded oil and gas pipelines using machine learning: A systematic review
Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Jundika C. Kurnia, et al.
Engineering Failure Analysis (2021) Vol. 131, pp. 105810-105810
Closed Access | Times Cited: 115
A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems
Jianli Chen, Liang Zhang, Yanfei Li, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 161, pp. 112395-112395
Open Access | Times Cited: 107
Predicting energy consumption for residential buildings using ANN through parametric modeling
Emad Elbeltagi, Hossam Wefki
Energy Reports (2021) Vol. 7, pp. 2534-2545
Open Access | Times Cited: 106
Load Forecasting Techniques and Their Applications in Smart Grids
Hany Habbak, Mohamed Mahmoud, Khaled Metwally, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1480-1480
Open Access | Times Cited: 93
Operational carbon transition in the megalopolises’ commercial buildings
Minda Ma, Wei Feng, Jingwen Huo, et al.
Building and Environment (2022) Vol. 226, pp. 109705-109705
Closed Access | Times Cited: 75
Advances in corrosion growth modeling for oil and gas pipelines: A review
Haonan Ma, Weidong Zhang, Yao Wang, et al.
Process Safety and Environmental Protection (2022) Vol. 171, pp. 71-86
Closed Access | Times Cited: 70
Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction
Jin Li, Naiteng Wu, Jian Zhang, et al.
Nano-Micro Letters (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 67
Blockchain and Machine Learning for Future Smart Grids: A Review
Vidya Krishnan Mololoth, Saguna Saguna, Christer Åhlund
Energies (2023) Vol. 16, Iss. 1, pp. 528-528
Open Access | Times Cited: 63
Intelligent multiobjective optimization design for NZEBs in China: Four climatic regions
Xianguo Wu, Xinyi Li, Yawei Qin, et al.
Applied Energy (2023) Vol. 339, pp. 120934-120934
Closed Access | Times Cited: 55
Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review
Wadim Striełkowski, Andrey Vlasov, Kirill Selivanov, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4025-4025
Open Access | Times Cited: 55
Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead
Saima Akhtar, Sulman Shahzad, Asad Zaheer, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4060-4060
Open Access | Times Cited: 50
A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation
Mahmoud Elsisi, Mohammed Amer, Alya’ Dababat, et al.
Energy (2023) Vol. 281, pp. 128256-128256
Closed Access | Times Cited: 46
Automated machine learning-based framework of heating and cooling load prediction for quick residential building design
Chujie Lu, Sihui Li, Santhan Reddy Penaka, et al.
Energy (2023) Vol. 274, pp. 127334-127334
Closed Access | Times Cited: 45
Multi-objective optimization of residential building energy consumption, daylighting, and thermal comfort based on BO-XGBoost-NSGA-II
Chengjin Wu, Haize Pan, Zhenhua Luo, et al.
Building and Environment (2024) Vol. 254, pp. 111386-111386
Closed Access | Times Cited: 45
A review on enhancing energy efficiency and adaptability through system integration for smart buildings
Um-e-Habiba, Ijaz Ahmed, Mohammad Asif, et al.
Journal of Building Engineering (2024) Vol. 89, pp. 109354-109354
Closed Access | Times Cited: 32
Comprehensive Survey of Artificial Intelligence Techniques and Strategies for Climate Change Mitigation
Zahra Mohtasham‐Amiri, Arash Heidari, Nima Jafari Navimipour
Energy (2024) Vol. 308, pp. 132827-132827
Closed Access | Times Cited: 22
Explainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques – A Review
Lukas Baur, Konstantin Ditschuneit, Maximilian Schambach, et al.
Energy and AI (2024) Vol. 16, pp. 100358-100358
Open Access | Times Cited: 21
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