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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:

Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market
Dalil Hadjout, J. F. Torres, Alicia Troncoso, et al.
Energy (2021) Vol. 243, pp. 123060-123060
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting
Nebojša Bačanin, Cătălin Stoean, Miodrag Živković, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1434-1434
Open Access | Times Cited: 77
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: 61
A novel two-stage seasonal grey model for residential electricity consumption forecasting
Pei Du, Ju’e Guo, Shaolong Sun, et al.
Energy (2022) Vol. 258, pp. 124664-124664
Closed Access | Times Cited: 39
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
M. J. Jiménez-Navarro, M. Martínez-Ballesteros, Isabel Sofía Brito, et al.
(2023)
Open Access | Times Cited: 34
Residential energy consumption forecasting using deep learning models
Paulo Vitor Barbosa Ramos, Saulo Moraes Villela, Walquiria N. Silva, et al.
Applied Energy (2023) Vol. 350, pp. 121705-121705
Closed Access | Times Cited: 24
Uncertainty management in electricity demand forecasting with machine learning and ensemble learning: Case studies of COVID-19 in the US metropolitans
Mohammed Rashad Baker, Kamal H. Jihad, Hussein Al-bayaty, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106350-106350
Closed Access | Times Cited: 23
A GPU-accelerated adaptation of the PSO algorithm for multi-objective optimization applied to artificial neural networks to predict energy consumption
J. R. S. Iruela, L. G. B. Ruiz, D. Criado-Ramón, et al.
Applied Soft Computing (2024) Vol. 160, pp. 111711-111711
Closed Access | Times Cited: 8
Pulse-diagnosis-inspired multi-feature extraction deep network for short-term electricity load forecasting
Han Wu, Yan Liang, Jiani Heng
Applied Energy (2023) Vol. 339, pp. 120995-120995
Closed Access | Times Cited: 21
A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia
Ejigu Tefera Habtemariam, Kula Kekeba, M. Martínez-Ballesteros, et al.
Energies (2023) Vol. 16, Iss. 5, pp. 2317-2317
Open Access | Times Cited: 18
Long-term electricity demand forecasting under low-carbon energy transition: Based on the bidirectional feedback between power demand and generation mix
Haowei Jin, Ju’e Guo, T. T. Lei, et al.
Energy (2023) Vol. 286, pp. 129435-129435
Closed Access | Times Cited: 16
Enhancing hourly electricity forecasting using fuzzy cognitive maps with sample entropy
Shoujiang Li, Jianzhou Wang, Hui Zhang, et al.
Energy (2024) Vol. 298, pp. 131429-131429
Closed Access | Times Cited: 5
Leveraging advanced ensemble models to increase building energy performance prediction accuracy in the residential building sector
Koray Konhäuser, Simon Wenninger, Tim Werner, et al.
Energy and Buildings (2022) Vol. 269, pp. 112242-112242
Closed Access | Times Cited: 25
Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market
Dalil Hadjout, Abderrazak Sebaa, J. F. Torres, et al.
Expert Systems with Applications (2023) Vol. 227, pp. 120123-120123
Closed Access | Times Cited: 15
Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives
Lorena Espina-Romero, José Gregorio Noroño Sánchez, Humberto Gutiérrez Hurtado, et al.
Sustainability (2023) Vol. 15, Iss. 16, pp. 12176-12176
Open Access | Times Cited: 14
Electricity consumption forecasting for sustainable smart cities using machine learning methods
Darius Peteleaza, Alexandru Matei, Radu Sorostinean, et al.
Internet of Things (2024) Vol. 27, pp. 101322-101322
Open Access | Times Cited: 5
Predictive Analytics and Machine Learning for Electricity Consumption Resilience in Wholesale Power Markets
Jamshaid Iqbal Janjua, Adeel Sabir, Tahir Abbas, et al.
(2024), pp. 1-7
Closed Access | Times Cited: 4
Deep learning-based novel ensemble method with best score transferred-adaptive neuro fuzzy inference system for energy consumption prediction
Birce Dağkurs, İsmail Atacak
PeerJ Computer Science (2025) Vol. 11, pp. e2680-e2680
Open Access
A novel multivariate nonlinear time-delayed grey model for forecasting electricity consumption
Wen-Ze Wu, Naiming Xie
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110452-110452
Closed Access
Optimal control method of regional power grid based on elastic carrying capacity analysis and day-ahead evaluation
Yu Zhang, Qingsheng Li
Energy Informatics (2025) Vol. 8, Iss. 1
Open Access
Energy consumption optimization of building air conditioning system via combining the parallel temporal convolutional neural network and adaptive opposition-learning chimp algorithm
Hongchang Sun, Yanlei Niu, Chengdong Li, et al.
Energy (2022) Vol. 259, pp. 125029-125029
Closed Access | Times Cited: 19
Big multi-step ship motion forecasting using a novel hybrid model based on real-time decomposition, boosting algorithm and error correction framework
Yunyu Wei, Zezong Chen, Chen Zhao, et al.
Ocean Engineering (2022) Vol. 256, pp. 111471-111471
Closed Access | Times Cited: 16
Variable Split Convolutional Attention: A novel Deep Learning model applied to the household electric power consumption
Rui Gonçalves, Vítor Miguel Ribeiro, Фернандо Лобо Перейра
Energy (2023) Vol. 274, pp. 127321-127321
Open Access | Times Cited: 10
Use of Kiwi Waste as Fuel in MFC and Its Potential for Use as Renewable Energy
Segundo Rojas-Flores, Magaly De La Cruz-Noriega, Luis Cabanillas-Chirinos, et al.
Fermentation (2023) Vol. 9, Iss. 5, pp. 446-446
Open Access | Times Cited: 10
Forecasting Regional Energy Consumption via Jellyfish Search-Optimized Convolutional-Based Deep Learning
Jui‐Sheng Chou, Ngoc-Quang Nguyen
International Journal of Energy Research (2023) Vol. 2023, pp. 1-25
Open Access | Times Cited: 10
Electricity demand forecasting based on feature extraction and optimized backpropagation neural network
Eric Ofori-Ntow, Yao Yevenyo Ziggah
e-Prime - Advances in Electrical Engineering Electronics and Energy (2023) Vol. 6, pp. 100293-100293
Open Access | Times Cited: 10
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