Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Uncertain wind power forecasting using LSTM‐based prediction interval
Abhishek Banik, Chinmay Kumar Behera, Tirunagaru V. Sarathkumar, et al.
IET Renewable Power Generation (2020) Vol. 14, Iss. 14, pp. 2657-2667
Closed Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

A review of wind speed and wind power forecasting with deep neural networks
Yun Wang, Runmin Zou, Fang Liu, et al.
Applied Energy (2021) Vol. 304, pp. 117766-117766
Closed Access | Times Cited: 569
New developments in wind energy forecasting with artificial intelligence and big data: a scientometric insight
Erlong Zhao, Shaolong Sun, Shouyang Wang
Data Science and Management (2022) Vol. 5, Iss. 2, pp. 84-95
Open Access | Times Cited: 123
Ultra-short-term forecasting of wind power based on multi-task learning and LSTM
Junqiang Wei, Xuejie Wu, Tianming Yang, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 149, pp. 109073-109073
Closed Access | Times Cited: 69
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Yun Wang, Houhua Xu, Mengmeng Song, et al.
Applied Energy (2023) Vol. 333, pp. 120601-120601
Closed Access | Times Cited: 64
Multi-Model Fusion Short-Term Load Forecasting Based on Random Forest Feature Selection and Hybrid Neural Network
Xuan Yi, Weiguo Si, Jiong Zhu, et al.
IEEE Access (2021) Vol. 9, pp. 69002-69009
Open Access | Times Cited: 88
Multi-Source and Temporal Attention Network for Probabilistic Wind Power Prediction
Hao Zhang, Jie Yan, Yongqian Liu, et al.
IEEE Transactions on Sustainable Energy (2021) Vol. 12, Iss. 4, pp. 2205-2218
Closed Access | Times Cited: 83
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: 50
Prediction of Air Pollution Interval Based on Data Preprocessing and Multi-Objective Dragonfly Optimization Algorithm
Jiyang Wang, Jingrui Li, Zhiwu Li
Frontiers in Ecology and Evolution (2022) Vol. 10
Open Access | Times Cited: 41
A hybrid prediction interval model for short-term electric load forecast using Holt-Winters and Gate Recurrent Unit
Xin He, Wenlu Zhao, Zhijun Gao, et al.
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101343-101343
Closed Access | Times Cited: 11
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
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: 35
Temporal collaborative attention for wind power forecasting
Yue Hu, Hanjing Liu, Senzhen Wu, et al.
Applied Energy (2023) Vol. 357, pp. 122502-122502
Open Access | Times Cited: 17
Development and trending of deep learning methods for wind power predictions
Hong Liu, Zijun Zhang
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 7
An innovative combined model based on multi-objective optimization approach for forecasting short-term wind speed: A case study in China
Jingrui Li, Jianzhou Wang, Haipeng Zhang, et al.
Renewable Energy (2022) Vol. 201, pp. 766-779
Closed Access | Times Cited: 23
Short-term wind speed forecasting based on a hybrid model of ICEEMDAN, MFE, LSTM and informer
Xinxin Wang, Shen Xiaopan, AI Xue-yi, et al.
PLoS ONE (2023) Vol. 18, Iss. 9, pp. e0289161-e0289161
Open Access | Times Cited: 14
CL-TGD: A novel point-wise contrastive learning with dynamic temporal granularity data incorporation for wind power prediction
Nanyang Zhu, Ning Jia, Wenjun Bi, et al.
Expert Systems with Applications (2025), pp. 126402-126402
Closed Access
Forecasting of virtual power plant generating and energy arbitrage economics in the electricity market using machine learning approach
Tirunagaru V. Sarathkumar, Arup Kumar Goswami, Baseem Khan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Probabilistic prediction of wind power based on QRNN and kernel density estimation
Xuejie Wu, Jun Liu, Kun Hu, et al.
Journal of Physics Conference Series (2025) Vol. 3000, Iss. 1, pp. 012018-012018
Open Access
Ultra-short-term wind power forecasting techniques: comparative analysis and future trends
Guangzheng Yu, Lingxu Shen, Qi Dong, et al.
Frontiers in Energy Research (2024) Vol. 11
Open Access | Times Cited: 3
Technical indicator enhanced ultra‐short‐term wind power forecasting based on long short‐term memory network combined XGBoost algorithm
Yingying Zheng, Shijie Guan, Kailei Guo, et al.
IET Renewable Power Generation (2024)
Open Access | Times Cited: 3
Predictive digital twin for wind energy systems: a literature review
Ege Kandemir, Agus Hasan, Trond Kvamsdal, et al.
Energy Informatics (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Enhanced offshore wind resource assessment using hybrid data fusion and numerical models
Basem Elshafei, Atanas A. Popov, Donald Giddings
Energy (2024), pp. 133208-133208
Open Access | Times Cited: 3
A deep reinforcement learning approach for wind speed forecasting
Shahab S. Band, T. Lin, Sultan Noman Qasem, et al.
Engineering Applications of Computational Fluid Mechanics (2025) Vol. 19, Iss. 1
Open Access
Predicting Wind Turbine Blade Tip Deformation With Long Short‐Term Memory (LSTM) Models
Shubham Baisthakur, Breiffni Fitzgerald
Wind Energy (2025) Vol. 28, Iss. 6
Open Access
A Forecasting Model of Wind Power Based on IPSO–LSTM and Classified Fusion
Qiuhong Huang, Xiao Wang
Energies (2022) Vol. 15, Iss. 15, pp. 5531-5531
Open Access | Times Cited: 13
Page 1 - Next Page

Scroll to top