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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 improved residual-based convolutional neural network for very short-term wind power forecasting
Ceyhun Yıldız, Hakan Açıkgöz, Deniz Korkmaz, et al.
Energy Conversion and Management (2020) Vol. 228, pp. 113731-113731
Closed Access | Times Cited: 198

Showing 51-75 of 198 citing articles:

Wind Power Prediction Based on Machine Learning and Deep Learning Models
Zahraa Tarek, Mahmoud Y. Shams, Ahmed M. Elshewey, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2022) Vol. 74, Iss. 1, pp. 715-732
Open Access | Times Cited: 37
A deep asymmetric Laplace neural network for deterministic and probabilistic wind power forecasting
Yun Wang, Houhua Xu, Runmin Zou, et al.
Renewable Energy (2022) Vol. 196, pp. 497-517
Closed Access | Times Cited: 35
Short-term wind power forecasting and uncertainty analysis based on FCM–WOA–ELM–GMM
Bo Gu, Hao Hu, Jian Zhao, et al.
Energy Reports (2022) Vol. 9, pp. 807-819
Open Access | Times Cited: 35
Wind Power Generation Forecast Based on Multi-Step Informer Network
Xiaohan Huang, Aihua Jiang
Energies (2022) Vol. 15, Iss. 18, pp. 6642-6642
Open Access | Times Cited: 34
Dynamic wind farm wake modeling based on a Bilateral Convolutional Neural Network and high-fidelity LES data
Rui Li, Jincheng Zhang, Xiaowei Zhao
Energy (2022) Vol. 258, pp. 124845-124845
Open Access | Times Cited: 32
A review of ultra-short-term forecasting of wind power based on data decomposition-forecasting technology combination model
Yulong Chen, Xue Hu, Lixin Zhang
Energy Reports (2022) Vol. 8, pp. 14200-14219
Open Access | Times Cited: 31
A novel series arc fault detection method for photovoltaic system based on multi-input neural network
Xiaoqi Chen, Wei Gao, Hong Cui, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 140, pp. 108018-108018
Closed Access | Times Cited: 30
Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Yinsong Chen, Samson S. Yu, Shama Naz Islam, et al.
Energy Reports (2022) Vol. 8, pp. 8805-8820
Open Access | Times Cited: 30
Wind Energy Harvesting and Conversion Systems: A Technical Review
Sinhara M. H. D. Perera, Ghanim Putrus, Michael Conlon, et al.
Energies (2022) Vol. 15, Iss. 24, pp. 9299-9299
Open Access | Times Cited: 30
Machine fault detection methods based on machine learning algorithms: A review
Giuseppe Ciaburro
Mathematical Biosciences & Engineering (2022) Vol. 19, Iss. 11, pp. 11453-11490
Open Access | Times Cited: 28
Short-Term Wind Power Forecasting Based on VMD and a Hybrid SSA-TCN-BiGRU Network
Yujie Zhang, Lei Zhang, Duo Sun, et al.
Applied Sciences (2023) Vol. 13, Iss. 17, pp. 9888-9888
Open Access | Times Cited: 21
A novel multi-layer stacking ensemble wind power prediction model under Tensorflow deep learning framework considering feature enhancement and data hierarchy processing
Huaqing Wang, Zhongfu Tan, Yan Liang, et al.
Energy (2023) Vol. 286, pp. 129409-129409
Closed Access | Times Cited: 21
Multi-modal multi-step wind power forecasting based on stacking deep learning model
Zhikai Xing, Yigang He
Renewable Energy (2023) Vol. 215, pp. 118991-118991
Closed Access | Times Cited: 19
Photovoltaic cell defect classification based on integration of residual-inception network and spatial pyramid pooling in electroluminescence images
Hakan Açıkgöz, Deniz Korkmaz, Ümit Budak
Expert Systems with Applications (2023) Vol. 229, pp. 120546-120546
Closed Access | Times Cited: 17
Risk assessment of customer churn in telco using FCLCNN-LSTM model
Cheng Wang, Congjun Rao, Fuyan Hu, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123352-123352
Closed Access | Times Cited: 7
A novel deep learning-based evolutionary model with potential attention and memory decay-enhancement strategy for short-term wind power point-interval forecasting
Zhi-Feng Liu, You-Yuan Liu, Xiaorui Chen, et al.
Applied Energy (2024) Vol. 360, pp. 122785-122785
Closed Access | Times Cited: 7
Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations
Mao Yang, Y. Huang, Chuanyu Xu, et al.
Applied Energy (2024) Vol. 377, pp. 124631-124631
Closed Access | Times Cited: 7
Research on the short-term wind power prediction with dual branch multi-source fusion strategy
Ling Tan, Yihe Chen, Jingming Xia, et al.
Energy (2024) Vol. 291, pp. 130402-130402
Closed Access | Times Cited: 6
Leveraging Deep Learning to Strengthen the Cyber-Resilience of Renewable Energy Supply Chains: A Survey
Malka N. Halgamuge
IEEE Communications Surveys & Tutorials (2024) Vol. 26, Iss. 3, pp. 2146-2175
Closed Access | Times Cited: 6
Long‐term scenario generation of renewable energy generation using attention‐based conditional generative adversarial networks
Hui Li, Haoyang Yu, Zhongjian Liu, et al.
Energy Conversion and Economics (2024) Vol. 5, Iss. 1, pp. 15-27
Closed Access | Times Cited: 6
An Efficient and Interpretable Stacked Model for Wind Speed Estimation Based on Ensemble Learning Algorithms
Ankit Jha, Vansh Goel, Manish Kumar, et al.
Energy Technology (2024) Vol. 12, Iss. 6
Closed Access | Times Cited: 6
3DTCN-CBAM-LSTM short-term power multi-step prediction model for offshore wind power based on data space and multi-field cluster spatio-temporal correlation
Ruoyun Du, Hongfei Chen, Min Yu, et al.
Applied Energy (2024) Vol. 376, pp. 124169-124169
Closed Access | Times Cited: 6
Short-term wind power prediction method based on multivariate signal decomposition and RIME optimization algorithm
Y. Wang, Lili Pei, Wei Li, et al.
Expert Systems with Applications (2024) Vol. 259, pp. 125376-125376
Closed Access | Times Cited: 6
Wind power forecasting based on time series model using deep machine learning algorithms
Chandran Venkatesan, Chandrashekhar K. Patil, Anto Merline Manoharan, et al.
Materials Today Proceedings (2021) Vol. 47, pp. 115-126
Closed Access | Times Cited: 38
A novel asexual-reproduction evolutionary neural network for wind power prediction based on generative adversarial networks
Hao Yin, Zuhong Ou, Zibin Zhu, et al.
Energy Conversion and Management (2021) Vol. 247, pp. 114714-114714
Closed Access | Times Cited: 37

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