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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:

Research and application of ensemble forecasting based on a novel multi-objective optimization algorithm for wind-speed forecasting
Zongxi Qu, Kequan Zhang, Wenqian Mao, et al.
Energy Conversion and Management (2017) Vol. 154, pp. 440-454
Closed Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

A review of deep learning for renewable energy forecasting
Huaizhi Wang, Zhenxing Lei, Xian Zhang, et al.
Energy Conversion and Management (2019) Vol. 198, pp. 111799-111799
Closed Access | Times Cited: 861
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
Tanveer Ahmad, Hongcai Zhang, Biao Yan
Sustainable Cities and Society (2020) Vol. 55, pp. 102052-102052
Closed Access | Times Cited: 368
Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods
Hui Liu, Chao Chen, Xinwei Lv, et al.
Energy Conversion and Management (2019) Vol. 195, pp. 328-345
Closed Access | Times Cited: 250
Day-ahead photovoltaic power forecasting approach based on deep convolutional neural networks and meta learning
Haixiang Zang, Lilin Cheng, Tao Ding, et al.
International Journal of Electrical Power & Energy Systems (2019) Vol. 118, pp. 105790-105790
Closed Access | Times Cited: 221
A review on meta-heuristics methods for estimating parameters of solar cells
Diego Oliva, Mohamed Abd Elaziz, Ammar H. Elsheikh, et al.
Journal of Power Sources (2019) Vol. 435, pp. 126683-126683
Closed Access | Times Cited: 177
Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network
Zongxi Qu, Wenqian Mao, Kequan Zhang, et al.
Renewable Energy (2018) Vol. 133, pp. 919-929
Closed Access | Times Cited: 163
A review on multi-objective optimization framework in wind energy forecasting techniques and applications
Hui Liu, Ye Li, Zhu Duan, et al.
Energy Conversion and Management (2020) Vol. 224, pp. 113324-113324
Closed Access | Times Cited: 154
A new hybrid ensemble deep reinforcement learning model for wind speed short term forecasting
Hui Liu, Chengqing Yu, Haiping Wu, et al.
Energy (2020) Vol. 202, pp. 117794-117794
Closed Access | Times Cited: 145
A long-term prediction approach based on long short-term memory neural networks with automatic parameter optimization by Tree-structured Parzen Estimator and applied to time-series data of NPP steam generators
Hoang-Phuong Nguyen, Jie Liu, Enrico Zio
Applied Soft Computing (2020) Vol. 89, pp. 106116-106116
Open Access | Times Cited: 137
Knowledge structure and research progress in wind power generation (WPG) from 2005 to 2020 using CiteSpace based scientometric analysis
Ali Azam, Ammar Ahmed, Hao Wang, et al.
Journal of Cleaner Production (2021) Vol. 295, pp. 126496-126496
Closed Access | Times Cited: 131
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
Peng Lu, Lin Ye, Yongning Zhao, et al.
Applied Energy (2021) Vol. 301, pp. 117446-117446
Closed Access | Times Cited: 129
Multi-head attention-based probabilistic CNN-BiLSTM for day-ahead wind speed forecasting
Yiming Zhang, Hao Wang
Energy (2023) Vol. 278, pp. 127865-127865
Closed Access | Times Cited: 80
Smart wind speed forecasting using EWT decomposition, GWO evolutionary optimization, RELM learning and IEWT reconstruction
Hui Liu, Haiping Wu, Yanfei Li
Energy Conversion and Management (2018) Vol. 161, pp. 266-283
Closed Access | Times Cited: 109
Smart wind speed forecasting approach using various boosting algorithms, big multi-step forecasting strategy
Yanfei Li, Huipeng Shi, Feng-ze Han, et al.
Renewable Energy (2018) Vol. 135, pp. 540-553
Closed Access | Times Cited: 106
Ensemble wind speed forecasting with multi-objective Archimedes optimization algorithm and sub-model selection
Lifang Zhang, Jianzhou Wang, Xinsong Niu, et al.
Applied Energy (2021) Vol. 301, pp. 117449-117449
Closed Access | Times Cited: 90
An adaptive hybrid model for short term wind speed forecasting
Jinliang Zhang, Yi‐Ming Wei, Zhongfu Tan
Energy (2019) Vol. 190, pp. 115615-115615
Closed Access | Times Cited: 86
Ensemble learning by means of a multi-objective optimization design approach for dealing with imbalanced data sets
Víctor Henrique Alves Ribeiro, Gilberto Reynoso-Meza
Expert Systems with Applications (2020) Vol. 147, pp. 113232-113232
Closed Access | Times Cited: 80
Comparison of eight filter-based feature selection methods for monthly streamflow forecasting – Three case studies on CAMELS data sets
Kun Ren, Wei Fang, Jihong Qu, et al.
Journal of Hydrology (2020) Vol. 586, pp. 124897-124897
Closed Access | Times Cited: 75
Dynamic ensemble wind speed prediction model based on hybrid deep reinforcement learning
Chao Chen, Hui Liu
Advanced Engineering Informatics (2021) Vol. 48, pp. 101290-101290
Closed Access | Times Cited: 63
Probabilistic wind power forecasting using selective ensemble of finite mixture Gaussian process regression models
Huaiping Jin, Lixian Shi, Xiangguang Chen, et al.
Renewable Energy (2021) Vol. 174, pp. 1-18
Closed Access | Times Cited: 61
Sizing and forecasting techniques in photovoltaic-wind based hybrid renewable energy system: A review
Ajay Kumar Bansal
Journal of Cleaner Production (2022) Vol. 369, pp. 133376-133376
Closed Access | Times Cited: 52
Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting
Wendong Yang, Mengying Hao, Hao Yan
Information Sciences (2022) Vol. 622, pp. 560-586
Closed Access | Times Cited: 41
Renewables integration into power systems through intelligent techniques: Implementation procedures, key features, and performance evaluation
Sayemul Islam, Naruttam Kumar Roy
Energy Reports (2023) Vol. 9, pp. 6063-6087
Open Access | Times Cited: 26
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: 11
Echo state network based ensemble approach for wind power forecasting
Huaizhi Wang, Zhenxing Lei, Yang Liu, et al.
Energy Conversion and Management (2019) Vol. 201, pp. 112188-112188
Closed Access | Times Cited: 71
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