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:

A new distributed decomposition–reconstruction–ensemble learning paradigm for short-term wind power prediction
Xixuan Zhao, Bingzhen Sun, Ruibin Geng
Journal of Cleaner Production (2023) Vol. 423, pp. 138676-138676
Closed Access | Times Cited: 12

Showing 12 citing articles:

Two-stage Day-ahead Multi-step Prediction of Wind Power Considering Time-series Information Interaction
Mao Yang, Xiangyu Li, Fulin Fan, et al.
Energy (2024) Vol. 312, pp. 133580-133580
Closed Access | Times Cited: 27
Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy
Xiaodi Wang, Hao Yan, Wendong Yang
Energy (2024) Vol. 297, pp. 131142-131142
Closed Access | Times Cited: 14
An adaptive distribution-matched recurrent network for wind power prediction using time-series distribution period division
Anbo Meng, Haitao Zhang, Zhongfu Dai, et al.
Energy (2024) Vol. 299, pp. 131383-131383
Closed Access | Times Cited: 8
STELLM: Spatio-temporal enhanced pre-trained large language model for wind speed forecasting
Tangjie Wu, Qiang Ling
Applied Energy (2024) Vol. 375, pp. 124034-124034
Closed Access | Times Cited: 8
A new multi-objective ensemble wind speed forecasting system: Mixed-frequency interval-valued modeling paradigm
Wendong Yang, Xinyi Zang, C.L. Wu, et al.
Energy (2024) Vol. 304, pp. 131963-131963
Closed Access | Times Cited: 5
A new multivariate decomposition-ensemble approach with denoised neighborhood rough set for stock price forecasting over time-series information system
Juncheng Bai, Bingzhen Sun, Yuqi Guo, et al.
Applied Intelligence (2025) Vol. 55, Iss. 4
Closed Access
A new short-term wind power prediction methodology based on linear and nonlinear hybrid models
Xixuan Zhao, Bingzhen Sun, Ning Wu, et al.
Computers & Industrial Engineering (2024) Vol. 196, pp. 110477-110477
Closed Access | Times Cited: 3
Kernel multi-granularity double-quantitative rough set based on ensemble empirical mode decomposition: Application to stock price trends prediction
Lin Zhang, Juncheng Bai, Bingzhen Sun, et al.
International Journal of Approximate Reasoning (2024) Vol. 172, pp. 109217-109217
Closed Access | Times Cited: 1
Using stacking ensemble learning to predict multi-step wind speed based on wavelet transformation, two-steps feature selection method, and neural networks
Faezeh Amirteimoury, Gholamreza Memarzadeh, Farshid Keynia
Measurement (2024) Vol. 244, pp. 116500-116500
Closed Access | Times Cited: 1
Wind turbine output power prediction by a segmented multivariate polynomial-XGBoost model
Jingwei Wang, Wangqiang Niu, Yanhua Yang
Energy Sources Part A Recovery Utilization and Environmental Effects (2023) Vol. 46, Iss. 1, pp. 505-521
Closed Access | Times Cited: 3
Using Stacking Ensemble Learning to Predict Multi-Step Wind Speed Based on Wavelet Transformation, a Two-Steps Feature Selection Method, and Neural Networks
Faezeh Amirteimoury, Gholamreza Memarzadeh, Farshid Keynia
(2024)
Closed Access
Probabilistic Forecasting of Multiple Plant Day-ahead Renewable Power Generation Sequences with Data Privacy Preserving
Hong Liu, Zijun Zhang
Energy and AI (2024), pp. 100463-100463
Open Access
Page 1

Scroll to top