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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:

Combined forecasting models for wind energy forecasting: A case study in China
Ling Xiao, Jianzhou Wang, Yao Dong, et al.
Renewable and Sustainable Energy Reviews (2015) Vol. 44, pp. 271-288
Closed Access | Times Cited: 180

Showing 1-25 of 180 citing articles:

A review of combined approaches for prediction of short-term wind speed and power
Akın Taşçıkaraoğlu, M. Uzunoglu
Renewable and Sustainable Energy Reviews (2014) Vol. 34, pp. 243-254
Closed Access | Times Cited: 599
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: 545
Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization
Jie Chen, Guo‐Qiang Zeng, Wuneng Zhou, et al.
Energy Conversion and Management (2018) Vol. 165, pp. 681-695
Closed Access | Times Cited: 365
A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting
Wenyu Zhang, Zongxi Qu, Kequan Zhang, et al.
Energy Conversion and Management (2017) Vol. 136, pp. 439-451
Closed Access | Times Cited: 336
A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
Zheng Qian, Yan Pei, Hamidreza Zareipour, et al.
Applied Energy (2018) Vol. 235, pp. 939-953
Closed Access | Times Cited: 332
A nonlinear hybrid wind speed forecasting model using LSTM network, hysteretic ELM and Differential Evolution algorithm
Ya-Lan Hu, Liang Chen
Energy Conversion and Management (2018) Vol. 173, pp. 123-142
Closed Access | Times Cited: 284
A data-driven multi-model methodology with deep feature selection for short-term wind forecasting
Cong Feng, Mingjian Cui, Bri‐Mathias Hodge, et al.
Applied Energy (2017) Vol. 190, pp. 1245-1257
Open Access | Times Cited: 282
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
A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting
Jingjing Song, Jianzhou Wang, Haiyan Lu
Applied Energy (2018) Vol. 215, pp. 643-658
Closed Access | Times Cited: 230
A Two-Layer Nonlinear Combination Method for Short-Term Wind Speed Prediction Based on ELM, ENN, and LSTM
Min-Rong Chen, Guo‐Qiang Zeng, Kang‐Di Lu, et al.
IEEE Internet of Things Journal (2019) Vol. 6, Iss. 4, pp. 6997-7010
Closed Access | Times Cited: 218
Hybrid structures in time series modeling and forecasting: A review
Zahra Hajirahimi, Mehdi Khashei
Engineering Applications of Artificial Intelligence (2019) Vol. 86, pp. 83-106
Closed Access | Times Cited: 185
An overview of global ocean wind energy resource evaluations
Chongwei Zheng, Chong Yin Li, Jing Pan, et al.
Renewable and Sustainable Energy Reviews (2015) Vol. 53, pp. 1240-1251
Closed Access | Times Cited: 184
Artificial Intelligence for Smart Renewable Energy Sector in Europe—Smart Energy Infrastructures for Next Generation Smart Cities
Andreea Claudia Șerban, Miltiadis D. Lytras
IEEE Access (2020) Vol. 8, pp. 77364-77377
Open Access | Times Cited: 177
A review of very short-term wind and solar power forecasting
Rosemary Tawn, Jethro Browell
Renewable and Sustainable Energy Reviews (2021) Vol. 153, pp. 111758-111758
Open Access | Times Cited: 176
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: 131
Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting
Pei Du, Jianzhou Wang, Zhenhai Guo, et al.
Energy Conversion and Management (2017) Vol. 150, pp. 90-107
Closed Access | Times Cited: 159
Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods
Yachao Zhang, Kaipei Liu, Liang Qin, et al.
Energy Conversion and Management (2016) Vol. 112, pp. 208-219
Closed Access | Times Cited: 153
A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting
Li‐Ye Xiao, Wei Shao, Tu-Lu Liang, et al.
Applied Energy (2016) Vol. 167, pp. 135-153
Closed Access | Times Cited: 141
Research and application of a combined model based on variable weight for short term wind speed forecasting
Hongmin Li, Jianzhou Wang, Haiyan Lu, et al.
Renewable Energy (2017) Vol. 116, pp. 669-684
Open Access | Times Cited: 140
Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron
Jihoon Moon, Yongsung Kim, Minjae Son, et al.
Energies (2018) Vol. 11, Iss. 12, pp. 3283-3283
Open Access | Times Cited: 130
EnLSTM-WPEO: Short-Term Traffic Flow Prediction by Ensemble LSTM, NNCT Weight Integration, and Population Extremal Optimization
Feixiang Zhao, Guo‐Qiang Zeng, Kang‐Di Lu
IEEE Transactions on Vehicular Technology (2019) Vol. 69, Iss. 1, pp. 101-113
Closed Access | Times Cited: 127
Current advances and approaches in wind speed and wind power forecasting for improved renewable energy integration: A review
Santhosh Madasthu, Chintham Venkaiah, D. M. Vinod Kumar
Engineering Reports (2020) Vol. 2, Iss. 6
Open Access | Times Cited: 120
A novel hybrid methodology for short-term wind power forecasting based on adaptive neuro-fuzzy inference system
Jinqiang Liu, Xiaoru Wang, Yun Lu
Renewable Energy (2016) Vol. 103, pp. 620-629
Open Access | Times Cited: 119
Non-parametric hybrid models for wind speed forecasting
Qinkai Han, Fanman Meng, Tao Hu, et al.
Energy Conversion and Management (2017) Vol. 148, pp. 554-568
Open Access | Times Cited: 113
Multi-objective algorithm for the design of prediction intervals for wind power forecasting model
Ping Jiang, Ranran Li, Hongmin Li
Applied Mathematical Modelling (2018) Vol. 67, pp. 101-122
Open Access | Times Cited: 113
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