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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.

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Showing 1-25 of 50 citing articles:

Deep learning for renewable energy forecasting: A taxonomy, and systematic literature review
Changtian Ying, Weiqing Wang, Jiong Yu, et al.
Journal of Cleaner Production (2022) Vol. 384, pp. 135414-135414
Closed Access | Times Cited: 72
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: 67
Ensemble system for short term carbon dioxide emissions forecasting based on multi-objective tangent search algorithm
Zhenkun Liu, Ping Jiang, Jianzhou Wang, et al.
Journal of Environmental Management (2021) Vol. 302, pp. 113951-113951
Closed Access | Times Cited: 86
Probabilistic Wind Power Forecasting Using Optimized Deep Auto-Regressive Recurrent Neural Networks
Parul Arora, Seyed Mohammad Jafar Jalali, Sajad Ahmadian, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 3, pp. 2814-2825
Closed Access | Times Cited: 48
Conformalized temporal convolutional quantile regression networks for wind power interval forecasting
Jianming Hu, Qingxi Luo, Jingwei Tang, et al.
Energy (2022) Vol. 248, pp. 123497-123497
Closed Access | Times Cited: 43
A novel wind power forecasting system integrating time series refining, nonlinear multi-objective optimized deep learning and linear error correction
Jianzhou Wang, Yuansheng Qian, Linyue Zhang, et al.
Energy Conversion and Management (2023) Vol. 299, pp. 117818-117818
Closed Access | Times Cited: 38
Hybrid ultra-short-term PV power forecasting system for deterministic forecasting and uncertainty analysis
Jianzhou Wang, Yue Yu, Bo Zeng, et al.
Energy (2023) Vol. 288, pp. 129898-129898
Closed Access | Times Cited: 24
A new perspective of wind speed forecasting: Multi-objective and model selection-based ensemble interval-valued wind speed forecasting system
Hao Yan, Xiaodi Wang, Jianzhou Wang, et al.
Energy Conversion and Management (2023) Vol. 299, pp. 117868-117868
Closed Access | Times Cited: 22
A novel wind power deterministic and interval prediction framework based on the critic weight method, improved northern goshawk optimization, and kernel density estimation
Guolian Hou, Junjie Wang, Yuzhen Fan, et al.
Renewable Energy (2024) Vol. 226, pp. 120360-120360
Closed Access | Times Cited: 11
A newly combination model based on data denoising strategy and advanced optimization algorithm for short-term wind speed prediction
Mengzheng Lv, Jianzhou Wang, Xinsong Niu, et al.
Journal of Ambient Intelligence and Humanized Computing (2022) Vol. 14, Iss. 7, pp. 8271-8290
Closed Access | Times Cited: 32
Research of a novel short-term wind forecasting system based on multi-objective Aquila optimizer for point and interval forecast
Qianyi Xing, Jianzhou Wang, Haiyan Lu, et al.
Energy Conversion and Management (2022) Vol. 263, pp. 115583-115583
Closed Access | Times Cited: 32
An Effective Optimization Algorithm for Parameters Identification of Photovoltaic Models
Behdad Arandian, Mahdiyeh Eslami, S.N. Khalid, et al.
IEEE Access (2022) Vol. 10, pp. 34069-34084
Open Access | Times Cited: 30
Regression model for predicting the speed of wind flows for energy needs based on fuzzy logic
Nasrullo Khasanzoda, Inga Zicmane, Svetlana Beryozkina, et al.
Renewable Energy (2022) Vol. 191, pp. 723-731
Closed Access | Times Cited: 30
Quantile regression based probabilistic forecasting of renewable energy generation and building electrical load: A state of the art review
Chengliang Xu, Yongjun Sun, Anran Du, et al.
Journal of Building Engineering (2023) Vol. 79, pp. 107772-107772
Closed Access | Times Cited: 18
An enhanced decomposition integration model for deterministic and probabilistic carbon price prediction based on two-stage feature extraction and intelligent weight optimization
Xin Zhang, Jujie Wang
Journal of Cleaner Production (2023) Vol. 415, pp. 137791-137791
Closed Access | Times Cited: 17
A wind speed prediction system based on new data preprocessing strategy and improved multi-objective optimizer
Zhirui Tian, Jiyang Wang
Renewable Energy (2023) Vol. 215, pp. 118932-118932
Closed Access | Times Cited: 17
A novel multivariate combined power load forecasting system based on feature selection and multi-objective intelligent optimization
Qianyi Xing, Xiaojia Huang, Jianzhou Wang, et al.
Expert Systems with Applications (2023) Vol. 244, pp. 122970-122970
Closed Access | Times Cited: 17
Advancements in wind power forecasting: A comprehensive review of artificial intelligence-based approaches
Krishan Kumar, Priti Prabhakar, Avnesh Verma, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 5
Uncertainty prediction of wind speed based on improved multi-strategy hybrid models
Xinyi Xu, Shaojuan Ma, Cheng Huang
Electronic Research Archive (2025) Vol. 33, Iss. 1, pp. 294-326
Open Access
A Comprehensive Review of the Tunicate Swarm Algorithm: Variations, Applications, and Results
Rong Zheng, Abdelazim G. Hussien, Anas Bouaouda, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case
Odin Foldvik Eikeland, Finn Dag Hovem, Tom Eirik Olsen, et al.
Energy Conversion and Management X (2022) Vol. 15, pp. 100239-100239
Open Access | Times Cited: 25
Novel deterministic and probabilistic combined system based on deep learning and self-improved optimization algorithm for wind speed forecasting
Mengzheng Lv, Jing Li, Xinsong Niu, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 52, pp. 102186-102186
Closed Access | Times Cited: 24
An Adaptive Tunicate Swarm Algorithm for Optimization of Shallow Foundation
Amirbahador Arabali, Mohammad Khajehzadeh, Suraparb Keawsawasvong, et al.
IEEE Access (2022) Vol. 10, pp. 39204-39219
Open Access | Times Cited: 23
Novel wind-speed prediction system based on dimensionality reduction and nonlinear weighting strategy for point-interval prediction
Xinyu Wang, Jianzhou Wang, Xinsong Niu, et al.
Expert Systems with Applications (2023) Vol. 241, pp. 122477-122477
Closed Access | Times Cited: 14
A fuzzy time series forecasting model with both accuracy and interpretability is used to forecast wind power
Xinjie Shi, Jianzhou Wang, Bochen Zhang
Applied Energy (2023) Vol. 353, pp. 122015-122015
Closed Access | Times Cited: 13
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