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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:

Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Dan Li, Fuxin Jiang, Min Chen, et al.
Energy (2021) Vol. 238, pp. 121981-121981
Closed Access | Times Cited: 138

Showing 1-25 of 138 citing articles:

Load Forecasting Techniques for Power System: Research Challenges and Survey
Naqash Ahmad, Yazeed Yasin Ghadi, Muhammad Adnan, et al.
IEEE Access (2022) Vol. 10, pp. 71054-71090
Open Access | Times Cited: 136
Efficient bootstrap stacking ensemble learning model applied to wind power generation forecasting
Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Sinvaldo Rodrigues Moreno, et al.
International Journal of Electrical Power & Energy Systems (2021) Vol. 136, pp. 107712-107712
Closed Access | Times Cited: 121
Ultra-short term wind power prediction applying a novel model named SATCN-LSTM
Ling Xiang, Jianing Liu, Xin Yang, et al.
Energy Conversion and Management (2021) Vol. 252, pp. 115036-115036
Closed Access | Times Cited: 110
An evolutionary deep learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM for wind speed prediction
Chu Zhang, Huixin Ma, Lei Hua, et al.
Energy (2022) Vol. 254, pp. 124250-124250
Closed Access | Times Cited: 99
Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization
Sheng-Xiang Lv, Lin Wang
Applied Energy (2022) Vol. 311, pp. 118674-118674
Closed Access | Times Cited: 87
A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error
Jikai Duan, Mingheng Chang, Xiangyue Chen, et al.
Renewable Energy (2022) Vol. 200, pp. 788-808
Closed Access | Times Cited: 82
Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition
Changrui Deng, Yanmei Huang, Najmul Hasan, et al.
Information Sciences (2022) Vol. 607, pp. 297-321
Closed Access | Times Cited: 77
Evolutionary quantile regression gated recurrent unit network based on variational mode decomposition, improved whale optimization algorithm for probabilistic short-term wind speed prediction
Chu Zhang, Chunlei Ji, Lei Hua, et al.
Renewable Energy (2022) Vol. 197, pp. 668-682
Closed Access | Times Cited: 70
Deep Learning for Time Series Forecasting: Advances and Open Problems
Angelo Casolaro, Vincenzo Capone, Gennaro Iannuzzo, et al.
Information (2023) Vol. 14, Iss. 11, pp. 598-598
Open Access | Times Cited: 45
Arctic short-term wind speed forecasting based on CNN-LSTM model with CEEMDAN
Qingyang Li, Guosong Wang, Xinrong Wu, et al.
Energy (2024) Vol. 299, pp. 131448-131448
Closed Access | Times Cited: 22
Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S
Xiaoying Sun, Haizhong Liu
Energy (2024) Vol. 305, pp. 132228-132228
Closed Access | Times Cited: 21
The univariate model for long-term wind speed forecasting based on wavelet soft threshold denoising and improved Autoformer
Guihua Ban, Yan Chen, Zhenhua Xiong, et al.
Energy (2024) Vol. 290, pp. 130225-130225
Closed Access | Times Cited: 19
Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks
Dan Li, Yijun Li, Chaoqun Wang, et al.
Applied Energy (2022) Vol. 331, pp. 120452-120452
Closed Access | Times Cited: 61
Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine
Emrah Dokur, Nuh Erdoğan, Mahdi Ebrahimi Salari, et al.
Energy (2022) Vol. 248, pp. 123595-123595
Open Access | Times Cited: 59
Review of load forecasting based on artificial intelligence methodologies, models, and challenges
Hui Hou, Chao Liu, Qing Wang, et al.
Electric Power Systems Research (2022) Vol. 210, pp. 108067-108067
Closed Access | Times Cited: 54
Wind power forecasting based on new hybrid model with TCN residual modification
Jiaojiao Zhu, Liancheng Su, Yingwei Li
Energy and AI (2022) Vol. 10, pp. 100199-100199
Open Access | Times Cited: 48
A novel combined forecasting model based on neural networks, deep learning approaches, and multi-objective optimization for short-term wind speed forecasting
Jianzhou Wang, Yining An, Zhiwu Li, et al.
Energy (2022) Vol. 251, pp. 123960-123960
Closed Access | Times Cited: 42
An online-learning-enabled self-attention-based model for ultra-short-term wind power forecasting
Xiaoran Dai, Shuai Liu, Wenshan Hu
Energy (2023) Vol. 272, pp. 127173-127173
Closed Access | Times Cited: 41
Hybrid model for short-term wind power forecasting based on singular spectrum analysis and a temporal convolutional attention network with an adaptive receptive field
Zhen Shao, Jun Han, Wei Zhao, et al.
Energy Conversion and Management (2022) Vol. 269, pp. 116138-116138
Closed Access | Times Cited: 40
Prediction of ultra-short-term wind power based on CEEMDAN-LSTM-TCN
Chenjia Hu, Yan Zhao, He Jiang, et al.
Energy Reports (2022) Vol. 8, pp. 483-492
Open Access | Times Cited: 39
Carbon price forecasting based on secondary decomposition and feature screening
Jingmiao Li, Dehong Liu
Energy (2023) Vol. 278, pp. 127783-127783
Closed Access | Times Cited: 35
IncepTCN: A new deep temporal convolutional network combined with dictionary learning for strong cultural noise elimination of controlled-source electromagnetic data
Guang Li, Shengzhuang Wu, Hongzhu Cai, et al.
Geophysics (2023) Vol. 88, Iss. 4, pp. E107-E122
Closed Access | Times Cited: 33
A compound framework incorporating improved outlier detection and correction, VMD, weight-based stacked generalization with enhanced DESMA for multi-step short-term wind speed forecasting
Wenlong Fu, Yuchen Fu, Bailing Li, et al.
Applied Energy (2023) Vol. 348, pp. 121587-121587
Closed Access | Times Cited: 32
Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research
Han Peng, Songyin Li, Linjian Shangguan, et al.
Sustainability (2023) Vol. 15, Iss. 10, pp. 8333-8333
Open Access | Times Cited: 30
Hydrogen leakage location prediction at hydrogen refueling stations based on deep learning
Yubo Bi, Qiulan Wu, Shilu Wang, et al.
Energy (2023) Vol. 284, pp. 129361-129361
Closed Access | Times Cited: 30
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