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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:

A new intelligent hybrid forecasting method for power load considering uncertainty
Guo‐Feng Fan, Ying-Ying Han, Jingjing Wang, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 111034-111034
Closed Access | Times Cited: 19

Showing 19 citing articles:

Forecasting the electric power load based on a novel prediction model coupled with accumulative time-delay effects and periodic fluctuation characteristics
Junjie Wang, Wenyu Huang, Yuanping Ding, et al.
Energy (2025), pp. 134518-134518
Closed Access | Times Cited: 1
A self-organizing deep network architecture designed based on LSTM network via elitism-driven roulette-wheel selection for time-series forecasting
Kun Zhou, Sung‐Kwun Oh, Witold Pedrycz, et al.
Knowledge-Based Systems (2024) Vol. 289, pp. 111481-111481
Closed Access | Times Cited: 9
The bi-long short-term memory based on multiscale and mesoscale feature extraction for electric load forecasting
Guo‐Feng Fan, Jinwei Li, Li‐Ling Peng, et al.
Applied Soft Computing (2024) Vol. 162, pp. 111853-111853
Closed Access | Times Cited: 6
An in-depth survey of the artificial gorilla troops optimizer: outcomes, variations, and applications
Abdelazim G. Hussien, Anas Bouaouda, Abdullah Alzaqebah, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 9
Open Access | Times Cited: 5
A power load forecasting method in port based on VMD-ICSS-hybrid neural network
Kai Ma, Xuefeng Nie, Jie Yang, et al.
Applied Energy (2024) Vol. 377, pp. 124246-124246
Closed Access | Times Cited: 5
Multivariate rolling decomposition hybrid learning paradigm for power load forecasting
Aiting Xu, Jiapeng Chen, Jinchang Li, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 212, pp. 115375-115375
Closed Access
Economic-environmental dispatch of isolated microgrids based on dynamic classification sparrow search algorithm
Guodong Xie, Mengjian Zhang, Deguang Wang, et al.
Expert Systems with Applications (2025) Vol. 271, pp. 126677-126677
Closed Access
A coupled framework for power load forecasting with Gaussian implicit spatio temporal block and attention mechanisms network
Dezhi Liu, Xuan Lin, Hanyang Liu, et al.
Computers & Electrical Engineering (2025) Vol. 123, pp. 110263-110263
Closed Access
Bilinear-DRTFT: Uncertainty prediction in electricity load considering multiple demand responses
Mengjie Xu, Qianwen Li, Zhengtang Zhao, et al.
Energy (2024) Vol. 309, pp. 133067-133067
Closed Access | Times Cited: 3
A hybrid load forecasting system based on data augmentation and ensemble learning under limited feature availability
Qing Yang, Zhirui Tian
Expert Systems with Applications (2024), pp. 125567-125567
Closed Access | Times Cited: 3
Sensitivity analysis and comparative assessment of novel hybridized boosting method for forecasting the power consumption
Jing Zhou, Qingdong Wang, Hamed Khajavi, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123631-123631
Closed Access | Times Cited: 2
Support vector machine-based stock market prediction using long short-term memory and convolutional neural network with aquila circle inspired optimization
J. Karthick Myilvahanan, N. Mohana Sundaram
Network Computation in Neural Systems (2024), pp. 1-36
Closed Access | Times Cited: 2
Predictive analysis of stochastic stock pattern utilizing fractional order dynamics and heteroscedastic with a radial neural network framework
Ayaz Hussain Bukhari, Muhammad Asif Zahoor Raja, Hani Alquhayz, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108687-108687
Closed Access | Times Cited: 2
Multi-Energy Load Short-Term Joint Forecasting of Integrated Energy System Based on Lstgn
Yuhang Fan, Qiongbin Lin, Ruochen Huang, et al.
(2024)
Closed Access | Times Cited: 1
Carbon Reduction in Modern Port: Novel Load Forecasting and Optimal Dispatching Methods for Integrated Port Energy System
Ruoli Tang, Siwen Ning, Zongyang Ren, et al.
(2024)
Closed Access
A Hybrid Power Load Forecasting Framework with Attention-Based Network and Multi-Scale Decomposition
Jiaming Zhu, Dezhi Liu, Lili Niu, et al.
(2024)
Closed Access
Enhancing Load Forecasting for Large Industrial Users Through Feature Preference and Error Correction
Zhaoguo Wang, Wenjie Li, Siteng Wang, et al.
IEEE Access (2024) Vol. 12, pp. 98647-98659
Open Access
Sleep-induced Network with Reducing Information Loss for Short-term Load Forecasting
Han Wu, Yan Liang, Xiao‐Zhi Gao, et al.
IEEE Transactions on Power Systems (2024) Vol. 40, Iss. 2, pp. 1492-1503
Closed Access
Short-term household power load forecasting based on ICEEMDAN decomposition and CNN-BiLSTM-SA hybrid model
Ruofeng Shen, Shuanglong Yang
Journal of Physics Conference Series (2024) Vol. 2823, Iss. 1, pp. 012053-012053
Open Access
A Short-Term Regional Net Load Prediction Method Based on Parallel Fragment Attention-BI-LSTM
Puxin Shi, Lin Geng, Mengfan Zhang, et al.
2022 IEEE 5th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) (2023), pp. 624-629
Closed Access | Times Cited: 1
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