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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:

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: 159

Showing 1-25 of 159 citing articles:

Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
Peijun Zheng, Heng Zhou, Jiang Liu, et al.
Applied Energy (2023) Vol. 349, pp. 121607-121607
Closed Access | Times Cited: 48
Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
Van Nhanh Nguyen, W. Tarełko, Prabhakar Sharma, et al.
Energy & Fuels (2024) Vol. 38, Iss. 3, pp. 1692-1712
Closed Access | Times Cited: 46
Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
The Science of The Total Environment (2023) Vol. 904, pp. 166960-166960
Closed Access | Times Cited: 44
Interpretation of convolutional neural network-based building HVAC fault diagnosis model using improved layer-wise relevance propagation
Guannan Li, Luhan Wang, Limei Shen, et al.
Energy and Buildings (2023) Vol. 286, pp. 112949-112949
Closed Access | Times Cited: 43
Multi-scale carbon emission characterization and prediction based on land use and interpretable machine learning model: A case study of the Yangtze River Delta Region, China
Haizhi Luo, Chenglong Wang, Cangbai Li, et al.
Applied Energy (2024) Vol. 360, pp. 122819-122819
Closed Access | Times Cited: 34
AI in HVAC fault detection and diagnosis: A systematic review
Jian Bi, Hua Wang, Enbo Yan, et al.
Energy Reviews (2024) Vol. 3, Iss. 2, pp. 100071-100071
Open Access | Times Cited: 26
An interpretable framework for modeling global solar radiation using tree-based ensemble machine learning and Shapley additive explanations methods
Zhe Song, Sunliang Cao, Hongxing Yang
Applied Energy (2024) Vol. 364, pp. 123238-123238
Closed Access | Times Cited: 21
Physics-informed neural networks for building thermal modeling and demand response control
Yongbao Chen, Qiguo Yang, Zhe Chen, et al.
Building and Environment (2023) Vol. 234, pp. 110149-110149
Closed Access | Times Cited: 40
AI-Driven Urban Energy Solutions—From Individuals to Society: A Review
Kinga Stecuła, Radosław Wolniak, Wieslaw Grebski
Energies (2023) Vol. 16, Iss. 24, pp. 7988-7988
Open Access | Times Cited: 35
Generative pre-trained transformers (GPT)-based automated data mining for building energy management: Advantages, limitations and the future
Chaobo Zhang, Jie Lu, Yang Zhao
Energy and Built Environment (2023) Vol. 5, Iss. 1, pp. 143-169
Open Access | Times Cited: 34
Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis
Julian Hoxha, Muhammed Yasin Çodur, Enea Mustafaraj, et al.
Applied Energy (2023) Vol. 350, pp. 121765-121765
Open Access | Times Cited: 30
Artificial intelligence enabled energy-efficient heating, ventilation and air conditioning system: Design, analysis and necessary hardware upgrades
Dasheng Lee, Shang-Tse Lee
Applied Thermal Engineering (2023) Vol. 235, pp. 121253-121253
Open Access | Times Cited: 29
Advancing Bridge Structural Health Monitoring: Insights into Knowledge-Driven and Data-Driven Approaches
Shuai Wan, Shuhong Guan, Yunchao Tang
Journal of Data Science and Intelligent Systems (2023) Vol. 2, Iss. 3, pp. 129-140
Open Access | Times Cited: 29
Lean and interpretable digital twins for building energy monitoring – A case study with smart thermostatic radiator valves and gas absorption heat pumps
Massimiliano Manfren, P.A.B. James, Victoria Aragón, et al.
Energy and AI (2023) Vol. 14, pp. 100304-100304
Open Access | Times Cited: 27
Melting of phase change materials inside metal foams with uniform/graded porosity: Pore-scale simulation
Tian Xiao, Zhao Du, Liu Lu, et al.
Applied Thermal Engineering (2023) Vol. 232, pp. 121082-121082
Closed Access | Times Cited: 25
How to improve the application potential of deep learning model in HVAC fault diagnosis: Based on pruning and interpretable deep learning method
Yuan Gao, Shohei Miyata, Yasunori Akashi
Applied Energy (2023) Vol. 348, pp. 121591-121591
Closed Access | Times Cited: 25
A Review of Building Energy Retrofit Measures, Passive Design Strategies and Building Regulation for the Low Carbon Development of Existing Dwellings in the Hot Summer–Cold Winter Region of China
Chenfei Liu, Steve Sharples, Haniyeh Mohammadpourkarbasi
Energies (2023) Vol. 16, Iss. 10, pp. 4115-4115
Open Access | Times Cited: 24
Energy flexibility quantification of a tropical net-zero office building using physically consistent neural network-based model predictive control
Wei Liang, Han Li, Sicheng Zhan, et al.
Advances in Applied Energy (2024) Vol. 14, pp. 100167-100167
Open Access | Times Cited: 13
Interpretability Research of Deep Learning: A Literature Survey
Biao Xu, Guanci Yang
Information Fusion (2024) Vol. 115, pp. 102721-102721
Closed Access | Times Cited: 12
Green building energy: Patents analysis and analytical hierarchy process evaluation
Omar Alharasees, Utku Kale, József Rohács, et al.
Heliyon (2024) Vol. 10, Iss. 8, pp. e29442-e29442
Open Access | Times Cited: 11
Machine learning applications on IoT data in manufacturing operations and their interpretability implications: A systematic literature review
Anna Presciuttini, Alessandra Cantini, Federica Costa, et al.
Journal of Manufacturing Systems (2024) Vol. 74, pp. 477-486
Open Access | Times Cited: 11
Innovative framework for accurate and transparent forecasting of energy consumption: A fusion of feature selection and interpretable machine learning
Hamidreza Eskandari, Hassan Saadatmand, Muhammad Ramzan, et al.
Applied Energy (2024) Vol. 366, pp. 123314-123314
Open Access | Times Cited: 11
Data Information integrated Neural Network (DINN) algorithm for modelling and interpretation performance analysis for energy systems
Waqar Muhammad Ashraf, Vivek Dua
Energy and AI (2024) Vol. 16, pp. 100363-100363
Open Access | Times Cited: 10
Interpretable feature selection and deep learning for short-term probabilistic PV power forecasting in buildings using local monitoring data
Heng Zhou, Peijun Zheng, Jiuqing Dong, et al.
Applied Energy (2024) Vol. 376, pp. 124271-124271
Closed Access | Times Cited: 10
Machine learning-based energy monitoring method applied to the HVAC systems electricity demand of an Italian healthcare facility
Marco Zini, Carlo Carcasci
Smart Energy (2024) Vol. 14, pp. 100137-100137
Open Access | Times Cited: 9
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