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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:

Short-term residential load forecasting using Graph Convolutional Recurrent Neural Networks
Sana Arastehfar, Mohammadjavad Matinkia, Mohammad Reza Jabbarpour
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105358-105358
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Wind speed interval prediction based on multidimensional time series of Convolutional Neural Networks
Jiyang Wang, Zhiwu Li
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105987-105987
Closed Access | Times Cited: 40
Deep learning-driven hybrid model for short-term load forecasting and smart grid information management
Xinyu Wen, Jiacheng Liao, Qingyi Niu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Machine Learning Applications in Building Energy Systems: Review and Prospects
D. Li, Zhenzhen Qi, Yiming Zhou, et al.
Buildings (2025) Vol. 15, Iss. 4, pp. 648-648
Open Access | Times Cited: 1
Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
Νικόλαος Γιαμαρέλος, Elias N. Zois
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101304-101304
Closed Access | Times Cited: 7
A short-term residential load forecasting scheme based on the multiple correlation-temporal graph neural networks
Yufeng Wang, Lingxiao Rui, Jianhua Ma, et al.
Applied Soft Computing (2023) Vol. 146, pp. 110629-110629
Closed Access | Times Cited: 16
Dynamic spatiotemporal interactive graph neural network for multivariate time series forecasting
Ziheng Gao, Zhuolin Li, Haoran Zhang, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 110995-110995
Closed Access | Times Cited: 16
Short-term load forecasting using spatial-temporal embedding graph neural network
Chuyuan Wei, Dechang Pi, Mingtian Ping, et al.
Electric Power Systems Research (2023) Vol. 225, pp. 109873-109873
Closed Access | Times Cited: 13
Power load forecasting based on spatial–temporal fusion graph convolution network
Jiang He, Yawei Dong, Yao Dong, et al.
Technological Forecasting and Social Change (2024) Vol. 204, pp. 123435-123435
Closed Access | Times Cited: 5
A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network
Geya Zhao, Minggao Xue, Li Cheng
Resources Policy (2023) Vol. 85, pp. 103956-103956
Closed Access | Times Cited: 12
Optimal expansion planning of electrical energy distribution substation considering hydrogen storage
Kıvanç Başaran, Hüseyin Öztürk
International Journal of Hydrogen Energy (2024) Vol. 75, pp. 450-465
Closed Access | Times Cited: 4
Day-ahead load forecast based on Conv2D-GRU_SC aimed to adapt to steep changes in load
Yunxiao Chen, Chaojing Lin, Yilan Zhang, et al.
Energy (2024) Vol. 302, pp. 131814-131814
Closed Access | Times Cited: 4
Multi-Building Energy Forecasting Through Weather-Integrated Temporal Graph Neural Networks
Samuel Moveh, Emmanuel Alejandro Merchán-Cruz, Maher Abuhussain, et al.
Buildings (2025) Vol. 15, Iss. 5, pp. 808-808
Open Access
Machine learning-driven load forecasting for urban energy optimization in morocco
Mouad Bensalah, Abdellatif Haïr
OPSEARCH (2025)
Closed Access
Application of a graph convolutional network for predicting the feasible operating regions of power to hydrogen facilities in integrated electricity and hydrogen-gas systems
Sheng Chen, Lei Zhu, Zhinong Wei, et al.
Energy (2025), pp. 136107-136107
Closed Access
Deep Learning for Forecasting-Based Applications in Cyber–Physical Microgrids: Recent Advances and Future Directions
Mohammad Reza Habibi, Saeed Golestan, Josep M. Guerrero, et al.
Electronics (2023) Vol. 12, Iss. 7, pp. 1685-1685
Open Access | Times Cited: 9
A hybrid prediction method for short‐term load based on temporal convolutional networks and attentional mechanisms
Min Li, Hangwei Tian, Qinghui Chen, et al.
IET Generation Transmission & Distribution (2023) Vol. 18, Iss. 5, pp. 885-898
Open Access | Times Cited: 8
Mining latent patterns with multi-scale decomposition for electricity demand and price forecasting using modified deep graph convolutional neural networks
Keerti Rawal, Aijaz Ahmad
Sustainable Energy Grids and Networks (2024) Vol. 39, pp. 101436-101436
Closed Access | Times Cited: 2
Spatio-temporal PV power forecasting considering the time-shift correction and the information fusion strategy of multi-stations
Xiyun Yang, Yang Yan, Lingzhuochao Meng, et al.
ISA Transactions (2023) Vol. 139, pp. 376-390
Closed Access | Times Cited: 5
Accurate identification and confidence evaluation of automatic generation control command execution effect based on deep learning fusion model
Guangyu Chen, Hongtong Liu, Haiyang Jiang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107819-107819
Closed Access | Times Cited: 1
Concurrent PV production and consumption load forecasting using CT‐Transformer deep learning to estimate energy system flexibility
Mohammad Zarghami, Taher Niknam, Jamshid Aghaei, et al.
IET Renewable Power Generation (2024) Vol. 18, Iss. 13, pp. 2139-2161
Open Access | Times Cited: 1
Multi-area short-term load forecasting based on spatiotemporal graph neural network
Yunlong Lv, Li Wang, Dunhua Long, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109398-109398
Closed Access | Times Cited: 1
Short‐term energy forecasting using deep neural networks: Prospects and challenges
Shewit Tsegaye, Sanjeevikumar Padmanaban, Lina Bertling Tjernberg, et al.
The Journal of Engineering (2024) Vol. 2024, Iss. 11
Open Access | Times Cited: 1
SmartFormer: Graph-based transformer model for energy load forecasting
Faisal Saeed, Abdul Rehman, Hasnain Ali Shah, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 73, pp. 104133-104133
Closed Access | Times Cited: 1
An Ensemble Deep Learning Model for Provincial Load Forecasting Based on Reduced Dimensional Clustering and Decomposition Strategies
Kaiyan Wang, Haodong Du, Jiao Wang, et al.
Mathematics (2023) Vol. 11, Iss. 12, pp. 2786-2786
Open Access | Times Cited: 2
Autoencoder Application for Anomaly Detection in Power Consumption of Lighting Systems
Tomasz Śmiałkowski, Andrzej Czyżewski
IEEE Access (2023) Vol. 11, pp. 124150-124162
Open Access | Times Cited: 2
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