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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.

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Showing 1-25 of 27 citing articles:

Design of IoT energy consumption forecasting model for residential buildings based on improved long short-term memory (LSTM)
Mustafa Wassef Hasan
Deleted Journal (2025), pp. 100033-100033
Open Access | Times Cited: 1
A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models
Hossein Abbasimehr, Reza Paki, Aram Bahrini
Sustainable Computing Informatics and Systems (2023) Vol. 38, pp. 100863-100863
Closed Access | Times Cited: 33
Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system
Mahdi Ghafoori, Moatassem Abdallah, Seo Young Kim
Applied Energy (2023) Vol. 340, pp. 121052-121052
Closed Access | Times Cited: 21
AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings
Dalia Mohammed Talat Ebrahim Ali, Violeta Motuzienė, Rasa Džiugaitė-Tumėnienė
Energies (2024) Vol. 17, Iss. 17, pp. 4277-4277
Open Access | Times Cited: 9
Implementation of a Long Short-Term Memory Transfer Learning (LSTM-TL)-Based Data-Driven Model for Building Energy Demand Forecasting
Dongsu Kim, Yongjun Lee, Kyungil Chin, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 2340-2340
Open Access | Times Cited: 16
BIM-Based Machine Learning Application for Parametric Assessment of Building Energy Performance
Panagiotis Tsikas, A.P. Chassiakos, Vasileios Papadimitropoulos, et al.
Energies (2025) Vol. 18, Iss. 1, pp. 201-201
Open Access
A comprehensive review and future research directions of ensemble learning models for predicting building energy consumption
Zeyu Wang, Yuelan Hong, Luying Huang, et al.
Energy and Buildings (2025), pp. 115589-115589
Closed Access
Predicting the PCM-incorporated building's performance using optimized linear kernel and tree-based machine learning methods
Kashif Nazir, Shazim Ali Memon, Assemgul Saurbayeva
Journal of Energy Storage (2024) Vol. 94, pp. 112495-112495
Closed Access | Times Cited: 4
Autoregressive Integrated Moving Average Model for Time Series Analysis
Dinesh Kumar Yadav, K Soumya, Laxmi Goswami
(2024), pp. 1-6
Closed Access | Times Cited: 3
A Review of Research on Building Energy Consumption Prediction Models Based on Artificial Neural Networks
Qing Yin, Chunmiao Han, Ailin Li, et al.
Sustainability (2024) Vol. 16, Iss. 17, pp. 7805-7805
Open Access | Times Cited: 3
Temperature Prediction of Seasonal Frozen Subgrades Based on CEEMDAN-LSTM Hybrid Model
Liyue Chen, Xiao Liu, Chao Zeng, et al.
Sensors (2022) Vol. 22, Iss. 15, pp. 5742-5742
Open Access | Times Cited: 15
Machine Learning Method Based on Symbiotic Organism Search Algorithm for Thermal Load Prediction in Buildings
Fatemeh Nejati, Wahidullah Omer Zoy, Nayer Tahoori, et al.
Buildings (2023) Vol. 13, Iss. 3, pp. 727-727
Open Access | Times Cited: 8
Sparse dynamic graph learning for district heat load forecasting
Yaohui Huang, Yuan Zhao, Zhijin Wang, et al.
Applied Energy (2024) Vol. 371, pp. 123685-123685
Open Access | Times Cited: 2
Behaviour of Machine Learning algorithms in the classification of energy consumption in school buildings
José Machado, António Chaves, Larissa Montenegro, et al.
Logic Journal of IGPL (2024)
Closed Access | Times Cited: 2
AI and Big Data-Empowered Low-Carbon Buildings: Challenges and Prospects
Huakun Huang, Dingrong Dai, Longtao Guo, et al.
Sustainability (2023) Vol. 15, Iss. 16, pp. 12332-12332
Open Access | Times Cited: 4
A Novel Hybrid Model (EMD-TI-LSTM) for Enhanced Financial Forecasting with Machine Learning
Olcay Ozupek, Reyat Yılmaz, Bita Ghasemkhani, et al.
Mathematics (2024) Vol. 12, Iss. 17, pp. 2794-2794
Open Access | Times Cited: 1
Modeling and validation of a novel load model considering uncertain thermal disturbance in the district heating system
Junhong Yang, Mengbo Peng, Tong Zhao, et al.
Energy and Buildings (2023) Vol. 289, pp. 113055-113055
Closed Access | Times Cited: 3
A simple load model based on hybrid mechanism and data-driven approach for district heating in building complex
Junhong Yang, Tong Zhao, Mengbo Peng, et al.
Energy and Buildings (2024) Vol. 322, pp. 114688-114688
Closed Access
Optimizing the Durability of Buildings Against Earthquake-Induced Collapse by the Implementation of Deep Learning-Based Control Strategy
Normaisharah Mamat, Rawad Abdulghafor, Sherzod Turaev, et al.
IEEE Access (2024) Vol. 12, pp. 121738-121752
Open Access
Energy Consumption Optimization in Data Centers Using LSTM-Based Load Prediction and Dynamic Resource Allocation
D Dang
Applied Mathematics and Nonlinear Sciences (2024) Vol. 9, Iss. 1
Open Access
Mutation types and pathogenicity classification using multi-label multi-class deep networks
Rana Saloom, Hussein K. Khafaji
AIP conference proceedings (2024) Vol. 3097, pp. 020004-020004
Closed Access
A novel improved hybrid neural network for predicting heating load in airport building
Zhilu Xue, Junqi Yu, Siyuan Yang, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110394-110394
Closed Access
Hourly Building Energy Consumption Prediction Using a Training Sample Selection Method Based on Key Feature Search
Haizhou Fang, Hongwei Tan, Ningfang Dai, et al.
Sustainability (2023) Vol. 15, Iss. 9, pp. 7458-7458
Open Access | Times Cited: 1
Do Large Datasets or Hybrid Integrated Models Outperform Simple Ones in Predicting Commodity Prices and Foreign Exchange Rates?
Jin Shang, Shigeyuki Hamori
Journal of risk and financial management (2023) Vol. 16, Iss. 6, pp. 298-298
Open Access | Times Cited: 1
Matching Prediction of Teacher Demand and Training Based on SARIMA Model Based on Neural Network
Jianliu Zhu
International Journal of Information Technology and Web Engineering (2023) Vol. 18, Iss. 1, pp. 1-15
Open Access | Times Cited: 1
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