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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 hybrid attention-based deep learning approach for wind power prediction
Zhengjing Ma, Gang Mei
Applied Energy (2022) Vol. 323, pp. 119608-119608
Closed Access | Times Cited: 100

Showing 1-25 of 100 citing articles:

Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism
Anping Wan, Qing Chang, Khalil AL-Bukhaiti, et al.
Energy (2023) Vol. 282, pp. 128274-128274
Closed Access | Times Cited: 162
A dual-scale deep learning model based on ELM-BiLSTM and improved reptile search algorithm for wind power prediction
Jinlin Xiong, Peng Tian, Zihan Tao, et al.
Energy (2022) Vol. 266, pp. 126419-126419
Closed Access | Times Cited: 151
State of health estimation for lithium-ion batteries based on hybrid attention and deep learning
Hongqian Zhao, Zheng Chen, Xing Shu, et al.
Reliability Engineering & System Safety (2022) Vol. 232, pp. 109066-109066
Closed Access | Times Cited: 71
Wavelet-Seq2Seq-LSTM with attention for time series forecasting of level of dams in hydroelectric power plants
Stéfano Frizzo Stefenon, Laio Oriel Seman, Luiza Scapinello Aquino, et al.
Energy (2023) Vol. 274, pp. 127350-127350
Closed Access | Times Cited: 66
A dual-optimization wind speed forecasting model based on deep learning and improved dung beetle optimization algorithm
Yanhui Li, Kaixuan Sun, Qi Yao, et al.
Energy (2023) Vol. 286, pp. 129604-129604
Closed Access | Times Cited: 66
A review of the applications of artificial intelligence in renewable energy systems: An approach-based study
Mersad Shoaei, Younes Noorollahi, Ahmad Hajinezhad, et al.
Energy Conversion and Management (2024) Vol. 306, pp. 118207-118207
Closed Access | Times Cited: 48
A hybrid photovoltaic/wind power prediction model based on Time2Vec, WDCNN and BiLSTM
Donghan Geng, Bo Wang, Qi Gao
Energy Conversion and Management (2023) Vol. 291, pp. 117342-117342
Closed Access | Times Cited: 42
A hybrid deep learning model based on parallel architecture TCN-LSTM with Savitzky-Golay filter for wind power prediction
Shujun Liu, Tong Xu, Xiaoze Du, et al.
Energy Conversion and Management (2024) Vol. 302, pp. 118122-118122
Closed Access | Times Cited: 32
Joint forecasting of source-load-price for integrated energy system based on multi-task learning and hybrid attention mechanism
Ke Li, Yuchen Mu, Fan Yang, et al.
Applied Energy (2024) Vol. 360, pp. 122821-122821
Closed Access | Times Cited: 19
Spatiotemporal wind power forecasting approach based on multi-factor extraction method and an indirect strategy
Shaolong Sun, Zongjuan Du, Kun Jin, et al.
Applied Energy (2023) Vol. 350, pp. 121749-121749
Closed Access | Times Cited: 34
Hybrid Inception-embedded deep neural network ResNet for short and medium-term PV-Wind forecasting
Adeel Feroz Mirza, Majad Mansoor, Muhammad Usman, et al.
Energy Conversion and Management (2023) Vol. 294, pp. 117574-117574
Closed Access | Times Cited: 34
A CNN encoder decoder LSTM model for sustainable wind power predictive analytics
Sherry Garg, Rajalakshmi Krishnamurthi
Sustainable Computing Informatics and Systems (2023) Vol. 38, pp. 100869-100869
Closed Access | Times Cited: 29
A Review of Modern Wind Power Generation Forecasting Technologies
Wen-Chang Tsai, Chih-Ming Hong, Chia‐Sheng Tu, et al.
Sustainability (2023) Vol. 15, Iss. 14, pp. 10757-10757
Open Access | Times Cited: 26
An improved attention-based deep learning approach for robust cooling load prediction: Public building cases under diverse occupancy schedules
Chujie Lu, Junhua Gu, Weizhuo Lu
Sustainable Cities and Society (2023) Vol. 96, pp. 104679-104679
Open Access | Times Cited: 22
A novel temporal–spatial graph neural network for wind power forecasting considering blockage effects
Hong Qiu, Kaikai Shi, Renfang Wang, et al.
Renewable Energy (2024) Vol. 227, pp. 120499-120499
Closed Access | Times Cited: 13
A hybrid wind speed prediction model using improved CEEMDAN and Autoformer model with auto-correlation mechanism
Bala Saibabu Bommidi, Kiran Teeparthi
Sustainable Energy Technologies and Assessments (2024) Vol. 64, pp. 103687-103687
Closed Access | Times Cited: 11
The Role of Utilizing Artificial Intelligence and Renewable Energy in Reaching Sustainable Development Goals
Fatma M. Talaat, A.E. Kabeel, Warda M. Shaban
Renewable Energy (2024) Vol. 235, pp. 121311-121311
Closed Access | Times Cited: 10
Prediction of blast furnace gas generation based on data quality improvement strategy
Shuhan Liu, Wenqiang Sun, Weidong Li, et al.
Journal of Iron and Steel Research International (2023) Vol. 30, Iss. 5, pp. 864-874
Closed Access | Times Cited: 22
A new demand response management strategy considering renewable energy prediction and filtering technology
Xidong Zheng, Feifei Bai, Zhiyuan Zhuang, et al.
Renewable Energy (2023) Vol. 211, pp. 656-668
Open Access | Times Cited: 21
VMD-CAT: A hybrid model for short-term wind power prediction
Huan Zheng, Zhenda Hu, Xuguang Wang, et al.
Energy Reports (2023) Vol. 9, pp. 199-211
Open Access | Times Cited: 20
Ultra-short-term wind power prediction method based on FTI-VACA-XGB model
Shijie Guan, Yongsheng Wang, Limin Liu, et al.
Expert Systems with Applications (2023) Vol. 235, pp. 121185-121185
Open Access | Times Cited: 20
Energy optimization of wind turbines via a neural control policy based on reinforcement learning Markov chain Monte Carlo algorithm
Vahid Tavakol Aghaei, Arda Ağababaoğlu, Biram Bawo, et al.
Applied Energy (2023) Vol. 341, pp. 121108-121108
Open Access | Times Cited: 17
TimeNet: Time2Vec attention-based CNN-BiGRU neural network for predicting production in shale and sandstone gas reservoirs
Mandella Ali M. Fargalla, Wei Qi Yan, Jingen Deng, et al.
Energy (2023) Vol. 290, pp. 130184-130184
Closed Access | Times Cited: 17
Chaos theory meets deep learning: A new approach to time series forecasting
Bowen Jia, Huyu Wu, Kaiyu Guo
Expert Systems with Applications (2024) Vol. 255, pp. 124533-124533
Closed Access | Times Cited: 7
An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model
Yunlong Lv, Qin Hu, Hang Xu, et al.
Energy (2024) Vol. 293, pp. 130751-130751
Closed Access | Times Cited: 6
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