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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:

Short‐term power load forecasting based on multi‐layer bidirectional recurrent neural network
Xianlun Tang, Yuyan Dai, Ting Wang, et al.
IET Generation Transmission & Distribution (2019) Vol. 13, Iss. 17, pp. 3847-3854
Closed Access | Times Cited: 138

Showing 1-25 of 138 citing articles:

Deep Learning for Time Series Forecasting: A Survey
J. F. Torres, Dalil Hadjout, Abderrazak Sebaa, et al.
Big Data (2020) Vol. 9, Iss. 1, pp. 3-21
Closed Access | Times Cited: 504
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
Abdullah Al Mamun, Md. Sohel, Naeem Mohammad, et al.
IEEE Access (2020) Vol. 8, pp. 134911-134939
Open Access | Times Cited: 252
Short-Term Load Forecasting for Industrial Customers Based on TCN-LightGBM
Yuanyuan Wang, Jun Chen, Xiaoqiao Chen, et al.
IEEE Transactions on Power Systems (2020) Vol. 36, Iss. 3, pp. 1984-1997
Closed Access | Times Cited: 250
Short term electricity load forecasting using hybrid prophet-LSTM model optimized by BPNN
Tasarruf Bashir, Haoyong Chen, Muhammad Faizan Tahir, et al.
Energy Reports (2022) Vol. 8, pp. 1678-1686
Open Access | Times Cited: 163
Short-Term Prediction of Residential Power Energy Consumption via CNN and Multi-Layer Bi-Directional LSTM Networks
Fath U Min Ullah, Amin Ullah, Ijaz Ul Haq, et al.
IEEE Access (2019) Vol. 8, pp. 123369-123380
Open Access | Times Cited: 162
Short-term load forecasting of industrial customers based on SVMD and XGBoost
Yuanyuan Wang, Shanfeng Sun, Xiaoqiao Chen, et al.
International Journal of Electrical Power & Energy Systems (2021) Vol. 129, pp. 106830-106830
Closed Access | Times Cited: 160
Convolutional and recurrent neural network based model for short-term load forecasting
Hosein Eskandari, Maryam Imani, Mohsen Parsa Moghaddam
Electric Power Systems Research (2021) Vol. 195, pp. 107173-107173
Closed Access | Times Cited: 137
Deep sequence to sequence Bi-LSTM neural networks for day-ahead peak load forecasting
Neelam Mughees, Syed Ali Mohsin, Abdullah Mughees, et al.
Expert Systems with Applications (2021) Vol. 175, pp. 114844-114844
Closed Access | Times Cited: 117
A deep LSTM network for the Spanish electricity consumption forecasting
J. F. Torres, Francisco Martínez‐Álvarez, Alicia Troncoso
Neural Computing and Applications (2022) Vol. 34, Iss. 13, pp. 10533-10545
Open Access | Times Cited: 83
Multi-Model Fusion Short-Term Load Forecasting Based on Random Forest Feature Selection and Hybrid Neural Network
Xuan Yi, Weiguo Si, Jiong Zhu, et al.
IEEE Access (2021) Vol. 9, pp. 69002-69009
Open Access | Times Cited: 85
Electrical Energy Prediction in Residential Buildings for Short-Term Horizons Using Hybrid Deep Learning Strategy
Zulfiqar Ahmad Khan, Amin Ullah, Waseem Ullah, et al.
Applied Sciences (2020) Vol. 10, Iss. 23, pp. 8634-8634
Open Access | Times Cited: 74
HSIC Bottleneck Based Distributed Deep Learning Model for Load Forecasting in Smart Grid With a Comprehensive Survey
Md. Akhtaruzzaman, Mohammad Kamrul Hasan, S. Rayhan Kabir, et al.
IEEE Access (2020) Vol. 8, pp. 222977-223008
Open Access | Times Cited: 73
Load Forecasting Under Concept Drift: Online Ensemble Learning With Recurrent Neural Network and ARIMA
Rashpinder Kaur Jagait, Mohammad Navid Fekri, Katarina Grolinger, et al.
IEEE Access (2021) Vol. 9, pp. 98992-99008
Open Access | Times Cited: 72
Hybrid short-term load forecasting using CGAN with CNN and semi-supervised regression
Xiangya Bu, Qiuwei Wu, Bin Zhou, et al.
Applied Energy (2023) Vol. 338, pp. 120920-120920
Closed Access | Times Cited: 28
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
Ensemble Model Based on Hybrid Deep Learning for Intrusion Detection in Smart Grid Networks
Ulaa AlHaddad, Abdullah Basuhail, Maher Khemakhem, et al.
Sensors (2023) Vol. 23, Iss. 17, pp. 7464-7464
Open Access | Times Cited: 21
Hybrid deep learning for power generation forecasting in active solar trackers
Stéfano Frizzo Stefenon, Christopher Kasburg, Ademir Nied, et al.
IET Generation Transmission & Distribution (2020) Vol. 14, Iss. 23, pp. 5667-5674
Open Access | Times Cited: 55
Spatiotemporal Behind-the-Meter Load and PV Power Forecasting via Deep Graph Dictionary Learning
Mahdi Khodayar, Guangyi Liu, Jianhui Wang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 10, pp. 4713-4727
Closed Access | Times Cited: 52
A novel framework for carbon price prediction using comprehensive feature screening, bidirectional gate recurrent unit and Gaussian process regression
Jujie Wang, Quan Cui, Xin Sun
Journal of Cleaner Production (2021) Vol. 314, pp. 128024-128024
Closed Access | Times Cited: 51
Aggregated short-term load forecasting for heterogeneous buildings using machine learning with peak estimation
Amine Bellahsen, Hanane Dagdougui
Energy and Buildings (2021) Vol. 237, pp. 110742-110742
Closed Access | Times Cited: 48
Short-term electricity demand forecasting via variational autoencoders and batch training-based bidirectional long short-term memory
Arash Moradzadeh, Hamed Moayyed, Kazem Zare, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 52, pp. 102209-102209
Closed Access | Times Cited: 31
A review on short‐term load forecasting models for micro‐grid application
V. Y. Kondaiah, B. Saravanan, Sanjeevikumar Padmanaban, et al.
The Journal of Engineering (2022) Vol. 2022, Iss. 7, pp. 665-689
Open Access | Times Cited: 27
Short term power load forecasting based on BES-VMD and CNN-Bi-LSTM method with error correction
Nier Wang, Zhanming Li
Frontiers in Energy Research (2023) Vol. 10
Open Access | Times Cited: 20
Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China
Md Jahidur Rahman, Hongtao Zhu
Accounting and Finance (2023) Vol. 63, Iss. 3, pp. 3455-3486
Open Access | Times Cited: 16
Enhanced industrial heat load forecasting in district networks via a multi-scale fusion ensemble deep learning
Zhiqiang Chen, Yang Yu, Chundi Jiang, et al.
Expert Systems with Applications (2025) Vol. 272, pp. 126783-126783
Closed Access
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