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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:

An effective dimensionality reduction approach for short-term load forecasting
Yang Yang, Zijin Wang, Yuchao Gao, et al.
Electric Power Systems Research (2022) Vol. 210, pp. 108150-108150
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Novel wind speed forecasting model based on a deep learning combined strategy in urban energy systems
Hao Yan, Wendong Yang, Kedong Yin
Expert Systems with Applications (2023) Vol. 219, pp. 119636-119636
Closed Access | Times Cited: 41
Energy Forecasting: A Comprehensive Review of Techniques and Technologies
Aristeidis Mystakidis, Paraskevas Koukaras, Nikolaos Tsalikidis, et al.
Energies (2024) Vol. 17, Iss. 7, pp. 1662-1662
Open Access | Times Cited: 24
A novel learning approach for short-term photovoltaic power forecasting - A review and case studies
Khaled Ferkous, Mawloud Guermoui, Sarra Menakh, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108502-108502
Closed Access | Times Cited: 20
Short-term power load forecasting using bidirectional gated recurrent units-based adaptive stacked autoencoder
Jizhe Dong, Yi-Wen Jiang, Peiguang Chen, et al.
International Journal of Electrical Power & Energy Systems (2025) Vol. 165, pp. 110459-110459
Closed Access | Times Cited: 1
A deep model for short-term load forecasting applying a stacked autoencoder based on LSTM supported by a multi-stage attention mechanism
Zahra Fazlipour, Elaheh Mashhour, Mahmood Joorabian
Applied Energy (2022) Vol. 327, pp. 120063-120063
Closed Access | Times Cited: 57
Energy generation forecasting: elevating performance with machine and deep learning
Aristeidis Mystakidis, Evangelia Ntozi, Konstantinos Afentoulis, et al.
Computing (2023) Vol. 105, Iss. 8, pp. 1623-1645
Open Access | Times Cited: 22
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: 8
An integrated federated learning algorithm for short-term load forecasting
Yang Yang, Zijin Wang, Shangrui Zhao, et al.
Electric Power Systems Research (2022) Vol. 214, pp. 108830-108830
Open Access | Times Cited: 35
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
Interpretable fake news detection with topic and deep variational models
Marjan Hosseini, Alireza Javadian Sabet, Suining He, et al.
Online Social Networks and Media (2023) Vol. 36, pp. 100249-100249
Open Access | Times Cited: 17
Generative probabilistic prediction of precipitation induced landslide deformation with variational autoencoder and gated recurrent unit
Wencheng Cai, Fuan Lan, Xianhao Huang, et al.
Frontiers in Earth Science (2024) Vol. 12
Open Access | Times Cited: 6
Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting
H. Bae, Jong-Seong Park, Jeong In Choi, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A Systematic Review of Building Energy Consumption Prediction: From Perspectives of Load Classification, Data-Driven Frameworks, and Future Directions
Guanzhong Chen, Shengze Lu, Shiyu Zhou, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3086-3086
Open Access
Accurate ultra-short-term load forecasting based on load characteristic decomposition and convolutional neural network with bidirectional long short-term memory model
Mingyue Zhang, Yang Han, Amr S. Zalhaf, et al.
Sustainable Energy Grids and Networks (2023) Vol. 35, pp. 101129-101129
Closed Access | Times Cited: 15
Energy Demand Forecasting and Optimizing Electric Systems for Developing Countries
Saadman S. Arnob, Abu Isha Md. Sadot Arefin, Ahmed Yousuf Saber, et al.
IEEE Access (2023) Vol. 11, pp. 39751-39775
Open Access | Times Cited: 12
Optimal placement of distributed generation in power distribution system and evaluating the losses and voltage using machine learning algorithms
Akanksha Jain, S. C. Gupta
Frontiers in Energy Research (2024) Vol. 12
Open Access | Times Cited: 3
Advances in Deep Learning Techniques for Short-term Energy Load Forecasting Applications: A Review
Radhika Chandrasekaran, Senthil Kumar Paramasivan
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 3
Uncertainty analysis of photovoltaic power generation system and intelligent coupling prediction
Guo‐Feng Fan, Yi-Wen Feng, Li‐Ling Peng, et al.
Renewable Energy (2024) Vol. 234, pp. 121174-121174
Closed Access | Times Cited: 3
High-precision air conditioning load forecasting model based on improved sparrow search algorithm
Xinyu Yang, Guofeng Zhou, Zhongjun Ren, et al.
Journal of Building Engineering (2024) Vol. 92, pp. 109809-109809
Closed Access | Times Cited: 2
A hybrid SVR with the firefly algorithm enhanced by a logarithmic spiral for electric load forecasting
Weiguo Zhang, Linlin Gu, Shi Yang, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 11
The forecasting of surface displacement for tunnel slopes utilizing the WD-IPSO-GRU model
Guoqing Ma, Xiaopeng Zang, Shitong Chen, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Robust autoregressive bidirectional gated recurrent units model for short-term power forecasting
Yang Yang, Zijin Wang, Shangrui Zhao, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109453-109453
Open Access | Times Cited: 1
Robust load feature extraction based secondary VMD novel short-term load demand forecasting framework
Miao Zhang, Guowei Xiao, Jianhang Lu, et al.
Electric Power Systems Research (2024) Vol. 239, pp. 111198-111198
Closed Access | Times Cited: 1
Sequence signal prediction and reconstruction for multi-energy load forecasting in integrated energy systems: A bi-level multi-task learning method
Chengchen Liao, Mao Tan, Kang Li, et al.
Energy (2024), pp. 133960-133960
Closed Access | Times Cited: 1
A Short-Term Power Load Forecasting Method of Based on the CEEMDAN-MVO-GRU
Taorong Jia, Yao Lixiao, Guoqing Yang, et al.
Sustainability (2022) Vol. 14, Iss. 24, pp. 16460-16460
Open Access | Times Cited: 5
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