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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:

Using enhanced crow search algorithm optimization-extreme learning machine model to forecast short-term wind power
Lingling Li, Zhifeng Liu, Ming‐Lang Tseng, et al.
Expert Systems with Applications (2021) Vol. 184, pp. 115579-115579
Open Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model
Dongxiao Niu, Lijie Sun, Min Yu, et al.
Energy (2022) Vol. 254, pp. 124384-124384
Closed Access | Times Cited: 109
Boosted ANFIS model using augmented marine predator algorithm with mutation operators for wind power forecasting
Mohammed A. A. Al‐qaness, Ahmed A. Ewees, Hong Fan, et al.
Applied Energy (2022) Vol. 314, pp. 118851-118851
Closed Access | Times Cited: 103
Multi-objective distributed generation hierarchical optimal planning in distribution network: Improved beluga whale optimization algorithm
Ling-Ling Li, Xing-Da Fan, Kuo‐Jui Wu, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121406-121406
Closed Access | Times Cited: 42
A review of short-term wind power generation forecasting methods in recent technological trends
Ezgi Arslan Tuncar, Şafak Sağlam, Bülent Oral
Energy Reports (2024) Vol. 12, pp. 197-209
Closed Access | Times Cited: 19
Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine
Emrah Dokur, Nuh Erdoğan, Mahdi Ebrahimi Salari, et al.
Energy (2022) Vol. 248, pp. 123595-123595
Open Access | Times Cited: 58
Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems
Muhammad Hamza Zafar, Noman Mujeeb Khan, Majad Mansoor, et al.
Energy Conversion and Management (2022) Vol. 258, pp. 115564-115564
Open Access | Times Cited: 49
Artificial intelligence enabled efficient power generation and emissions reduction underpinning net-zero goal from the coal-based power plants
Waqar Muhammad Ashraf, Ghulam Moeen Uddin, Hassan Afroze Ahmad, et al.
Energy Conversion and Management (2022) Vol. 268, pp. 116025-116025
Open Access | Times Cited: 47
State of charge estimation for lithium-ion batteries based on improved barnacle mating optimizer and support vector machine
Boying Liu, Haiyu Wang, Ming‐Lang Tseng, et al.
Journal of Energy Storage (2022) Vol. 55, pp. 105830-105830
Closed Access | Times Cited: 44
An overview of deterministic and probabilistic forecasting methods of wind energy
Yuying Xie, Chaoshun Li, Mengying Li, et al.
iScience (2022) Vol. 26, Iss. 1, pp. 105804-105804
Open Access | Times Cited: 42
Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting
Hüseyin Parmaksız, Uğur Yüzgeç, Emrah Dokur, et al.
Knowledge-Based Systems (2023) Vol. 268, pp. 110472-110472
Open Access | Times Cited: 29
Short-Term Wind Power Prediction by an Extreme Learning Machine Based on an Improved Hunter–Prey Optimization Algorithm
Xiangyue Wang, Li Ji, Lei Shao, et al.
Sustainability (2023) Vol. 15, Iss. 2, pp. 991-991
Open Access | Times Cited: 23
Optimized Forecasting Approach for Scheduling Wind Generation Plants and Maximizing Renewable Energy Utilization
Rahul Kumar, K. Sathiyasekar, N. Nagabhooshanam, et al.
Electric Power Components and Systems (2024), pp. 1-17
Closed Access | Times Cited: 8
Short-term wind speed forecasting system based on multivariate time series and multi-objective optimization
Zhihao Shang, Zhaoshuang He, Yao Chen, et al.
Energy (2021) Vol. 238, pp. 122024-122024
Closed Access | Times Cited: 53
Energy scheduling optimization of the integrated energy system with ground source heat pumps
Zhenglin Zhang, Huijuan Zhang, Bo Xie, et al.
Journal of Cleaner Production (2022) Vol. 365, pp. 132758-132758
Closed Access | Times Cited: 34
Fault diagnosis in wind turbines based on ANFIS and Takagi–Sugeno interval observers
Esvan-Jesús Pérez-Pérez, Francisco‐Ronay López‐Estrada, Vicenç Puig, et al.
Expert Systems with Applications (2022) Vol. 206, pp. 117698-117698
Closed Access | Times Cited: 32
Dwarf Mongoose Optimization with Machine-Learning-Driven Ransomware Detection in Internet of Things Environment
Khalid Alissa, Dalia H. Elkamchouchi, Khaled Tarmissi, et al.
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 9513-9513
Open Access | Times Cited: 28
Optimization of process parameters and performance for machining Inconel 718 in renewable dielectrics
Wuyi Ming, Xudong Guo, Guojun Zhang, et al.
Alexandria Engineering Journal (2023) Vol. 79, pp. 164-179
Open Access | Times Cited: 18
Research on the short-term wind power prediction with dual branch multi-source fusion strategy
Ling Tan, Yihe Chen, Jingming Xia, et al.
Energy (2024) Vol. 291, pp. 130402-130402
Closed Access | Times Cited: 6
Review of AI-Based Wind Prediction within Recent Three Years: 2021–2023
Dongran Song, Xiao Tan, Qian Huang, et al.
Energies (2024) Vol. 17, Iss. 6, pp. 1270-1270
Open Access | Times Cited: 6
3DTCN-CBAM-LSTM short-term power multi-step prediction model for offshore wind power based on data space and multi-field cluster spatio-temporal correlation
Ruoyun Du, Hongfei Chen, Min Yu, et al.
Applied Energy (2024) Vol. 376, pp. 124169-124169
Closed Access | Times Cited: 6
Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources
Adam Krechowicz, Maria Krechowicz, Katarzyna Poczęta
Energies (2022) Vol. 15, Iss. 23, pp. 9146-9146
Open Access | Times Cited: 26
Bagging ensemble-based novel data generation method for univariate time series forecasting
Donghwan Kim, Jun‐Geol Baek
Expert Systems with Applications (2022) Vol. 203, pp. 117366-117366
Closed Access | Times Cited: 24
Semi-supervised learning with graph convolutional extreme learning machines
Zijia Zhang, Yaoming Cai, Wenyin Gong
Expert Systems with Applications (2022) Vol. 213, pp. 119164-119164
Closed Access | Times Cited: 24
Deep attention ConvLSTM-based adaptive fusion of clear-sky physical prior knowledge and multivariable historical information for probabilistic prediction of photovoltaic power
Mingliang Bai, Yunxiao Chen, Xinyu Zhao, et al.
Expert Systems with Applications (2022) Vol. 202, pp. 117335-117335
Closed Access | Times Cited: 23
A novel network training approach for solving sample imbalance problem in wind power prediction
Anbo Meng, Zikang Xian, Hao Yin, et al.
Energy Conversion and Management (2023) Vol. 283, pp. 116935-116935
Closed Access | Times Cited: 16
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