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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:

Robust building energy consumption forecasting using an online learning approach with R ranger
Jihoon Moon, Sungwoo Park, Seungmin Rho, et al.
Journal of Building Engineering (2021) Vol. 47, pp. 103851-103851
Closed Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

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: 164
Short-term building electrical load forecasting using adaptive neuro-fuzzy inference system (ANFIS)
Chaouki Ghenaï, Omar Ahmed Al-Mufti, Omar Adil Mashkoor Al-Isawi, et al.
Journal of Building Engineering (2022) Vol. 52, pp. 104323-104323
Closed Access | Times Cited: 70
A comprehensive review on deep learning approaches for short-term load forecasting
Yavuz Eren, İbrahim Beklan Küçükdemiral
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 114031-114031
Open Access | Times Cited: 68
Building energy consumption prediction and optimization using different neural network-assisted models; comparison of different networks and optimization algorithms
Sadegh Afzal, Afshar Shokri, Behrooz M. Ziapour, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107356-107356
Closed Access | Times Cited: 40
Toward explainable electrical load forecasting of buildings: A comparative study of tree-based ensemble methods with Shapley values
Jihoon Moon, Seungmin Rho, Sung Wook Baik
Sustainable Energy Technologies and Assessments (2022) Vol. 54, pp. 102888-102888
Open Access | Times Cited: 34
Predicting nominal shear capacity of reinforced concrete wall in building by metaheuristics-optimized machine learning
Jui‐Sheng Chou, Chi‐Yun Liu, Handy Prayogo, et al.
Journal of Building Engineering (2022) Vol. 61, pp. 105046-105046
Closed Access | Times Cited: 30
Towards online monitoring of concrete dam displacement subject to time-varying environments: An improved sequential learning approach
Qiubing Ren, Heng Li, Mingchao Li, et al.
Advanced Engineering Informatics (2023) Vol. 55, pp. 101881-101881
Closed Access | Times Cited: 21
Machine Learning Approach to Predict Building Thermal Load Considering Feature Variable Dimensions: An Office Building Case Study
Yongbao Chen, Yunyang Ye, Jingnan Liu, et al.
Buildings (2023) Vol. 13, Iss. 2, pp. 312-312
Open Access | Times Cited: 19
Building energy loads prediction using bayesian-based metaheuristic optimized-explainable tree-based model
Babatunde Abiodun Salami, Sani I. Abba, Adeshina Adewale Adewumi, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02676-e02676
Open Access | Times Cited: 19
Joint energy management and trading among renewable integrated microgrids for combined cooling, heating, and power systems
Muhammad Tanveer Riaz, Sadiq Ahmad, Muhammad Naeem
Journal of Building Engineering (2023) Vol. 75, pp. 106921-106921
Closed Access | Times Cited: 17
BiGTA-Net: A Hybrid Deep Learning-Based Electrical Energy Forecasting Model for Building Energy Management Systems
Dayeong So, Jinyeong Oh, Insu Jeon, et al.
Systems (2023) Vol. 11, Iss. 9, pp. 456-456
Open Access | Times Cited: 17
A Future Direction of Machine Learning for Building Energy Management: Interpretable Models
Luca Gugliermetti, Fabrizio Cumo, Sofia Agostinelli
Energies (2024) Vol. 17, Iss. 3, pp. 700-700
Open Access | Times Cited: 7
Two-Stage Neural Network Optimization for Robust Solar Photovoltaic Forecasting
Jinyeong Oh, Dayeong So, Jaehyeok Jo, et al.
Electronics (2024) Vol. 13, Iss. 9, pp. 1659-1659
Open Access | Times Cited: 6
An Analysis of the Energy Consumption Forecasting Problem in Smart Buildings Using LSTM
Daniela Durand, José Aguilar, María D. R‐Moreno
Sustainability (2022) Vol. 14, Iss. 20, pp. 13358-13358
Open Access | Times Cited: 28
Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist
Jihoon Moon, Sungwoo Park, Seungmin Rho, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-20
Open Access | Times Cited: 19
Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting
C. Jeevakarunya, V. Manikandan
AIP Advances (2025) Vol. 15, Iss. 1
Open Access
Prediction and strategies of buildings’ energy consumption: A review of modeling approaches and energy-saving technologies
Fangzheng Li, Tengfei Peng, Jing Chen, et al.
International Journal of Green Energy (2025), pp. 1-36
Closed 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
Building HVAC Electric Load Demand Prediction: Balancing Learning Rate and Hidden Layers for Improved Model Performance
Meng Gao, Yamei Wang, Yue Qin, et al.
Deleted Journal (2025) Vol. 2, Iss. 2
Closed Access
SolarNexus: A deep learning framework for adaptive photovoltaic power generation forecasting and scalable management
Hyunsik Min, Byeongjoon Noh
Applied Energy (2025) Vol. 391, pp. 125848-125848
Closed Access
AI-Enhanced Automation of Building Energy Optimization Using a Hybrid Stacked Model and Genetic Algorithms: Experiments with Seven Machine Learning Techniques and a Deep Neural Network
Mohammad H. Mehraban, Samad M. E. Sepasgozar, Alireza Ghomimoghadam, et al.
Results in Engineering (2025), pp. 104994-104994
Open Access
RAID: Robust and Interpretable Daily Peak Load Forecasting via Multiple Deep Neural Networks and Shapley Values
Joohyun Jang, Woonyoung Jeong, Sang Min Kim, et al.
Sustainability (2023) Vol. 15, Iss. 8, pp. 6951-6951
Open Access | Times Cited: 10
Transfer learning-based adaptive recursive neural network for short-term non-stationary building heating load prediction
Yong Zhou, Xiang Li, Yanfeng Liu, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107271-107271
Closed Access | Times Cited: 9
Towards Sustainable Buildings: Predictive Modeling of Energy Consumption with Machine Learning
Zineb Zoubir, Houda ER-RETBY, Niima Es-sakali, et al.
Procedia Computer Science (2024) Vol. 236, pp. 59-66
Open Access | Times Cited: 3
Predicting variation of multipoint earth pressure in sealed chambers of shield tunneling machines based on hybrid deep learning
Xuanyu Liu, Ziwen Wang, Yudong Wang, et al.
Automation in Construction (2022) Vol. 143, pp. 104567-104567
Closed Access | Times Cited: 15
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