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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:

Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression
Mahdi Sharifzadeh, Alexandra Sikinioti-Lock, Nilay Shah
Renewable and Sustainable Energy Reviews (2019) Vol. 108, pp. 513-538
Closed Access | Times Cited: 295

Showing 51-75 of 295 citing articles:

Using different machine learning algorithms to predict the rheological behavior of oil SAE40-based nano-lubricant in the presence of MWCNT and MgO nanoparticles
Mohammadreza Baghoolizadeh, Navid Nasajpour-Esfahani, Mostafa Pirmoradian, et al.
Tribology International (2023) Vol. 187, pp. 108759-108759
Closed Access | Times Cited: 25
A review of machine learning and deep learning applications in wave energy forecasting and WEC optimization
Alireza Shadmani, Mohammad Reza Nikoo, Amir H. Gandomi, et al.
Energy Strategy Reviews (2023) Vol. 49, pp. 101180-101180
Open Access | Times Cited: 25
Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition
Yuekuan Zhou, Siqian Zheng, Jlm Jan Hensen
Renewable and Sustainable Energy Reviews (2024) Vol. 199, pp. 114466-114466
Closed Access | Times Cited: 15
Impacts of digitalization on smart grids, renewable energy, and demand response: An updated review of current applications
Mou Mahmood, Prangon Chowdhury, Rahbaar Yeassin, et al.
Energy Conversion and Management X (2024) Vol. 24, pp. 100790-100790
Open Access | Times Cited: 15
Renewable energy sources integration via machine learning modelling: A systematic literature review
Talal Alazemi, Mohamed Darwish, Mohammed Radi
Heliyon (2024) Vol. 10, Iss. 4, pp. e26088-e26088
Open Access | Times Cited: 14
Short-Term Load Forecasting: A Comprehensive Review and Simulation Study With CNN-LSTM Hybrids Approach
Kaleem Ullah, Muhammad Ahsan, Syed Muhammad Hasanat, et al.
IEEE Access (2024) Vol. 12, pp. 111858-111881
Open Access | Times Cited: 14
A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction
Mohammad Rostamzadeh‐Renani, Mohammadreza Baghoolizadeh, S. Mohammad Sajadi, et al.
Propulsion and Power Research (2024) Vol. 13, Iss. 1, pp. 26-45
Open Access | Times Cited: 13
Operational strategies and integrated design for producing green hydrogen from wind electricity
Mahdi Sharifzadeh, Nathanial J. Cooper, Hans van't Noordende, et al.
International Journal of Hydrogen Energy (2024) Vol. 64, pp. 650-675
Closed Access | Times Cited: 12
Optimization‐improved thermal–mechanical simulation of welding residual stresses in welded connections
Le Wang, Xudong Qian
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 9, pp. 1275-1293
Open Access | Times Cited: 11
Innovative framework for accurate and transparent forecasting of energy consumption: A fusion of feature selection and interpretable machine learning
Hamidreza Eskandari, Hassan Saadatmand, Muhammad Ramzan, et al.
Applied Energy (2024) Vol. 366, pp. 123314-123314
Open Access | Times Cited: 11
Machine learning prediction of bio-oil production from the pyrolysis of lignocellulosic biomass: Recent advances and future perspectives
Hyojin Lee, Il-Ho Choi, Kyung-Ran Hwang
Journal of Analytical and Applied Pyrolysis (2024) Vol. 179, pp. 106486-106486
Open Access | Times Cited: 10
Prediction and extensive analysis of MWCNT-MgO/oil SAE 50 hybrid nano-lubricant rheology utilizing machine learning and genetic algorithms to find ideal attributes
Mohammadreza Baghoolizadeh, Mostafa Pirmoradian, S. Mohammad Sajadi, et al.
Tribology International (2024) Vol. 195, pp. 109582-109582
Closed Access | Times Cited: 10
A novel data-driven machine learning techniques to predict compressive strength of fly ash and recycled coarse aggregates based self-compacting concrete
Surbhi Gupta Aggarwal, Rajwinder Singh, Ayush Rathore, et al.
Materials Today Communications (2024) Vol. 39, pp. 109294-109294
Closed Access | Times Cited: 10
Energy management system in networked microgrids: an overview
J. A. Rodriguez-Gil, Eduardo Mojica‐Nava, Daniel Vargas-Medina, et al.
Energy Systems (2024)
Open Access | Times Cited: 10
Comparative study on ballistic impact detection in helicopter transmission shafts using NARX and LSTM models
Vasiliki Panagiotopoulou, Lorenzo Brancato, Emanuele Petriconi, et al.
Applied Intelligence (2025) Vol. 55, Iss. 4
Closed Access | Times Cited: 1
Ensemble deep learning based semi-supervised soft sensor modeling method and its application on quality prediction for coal preparation process
Xianhui Yin, Zhanwen Niu, Zhen He, et al.
Advanced Engineering Informatics (2020) Vol. 46, pp. 101136-101136
Closed Access | Times Cited: 57
Household standards and socio-economic aspects as a factor determining energy consumption in the city
Maria Mrówczyńska, Marta Skiba, Anna Bazan-Krzywoszańska, et al.
Applied Energy (2020) Vol. 264, pp. 114680-114680
Open Access | Times Cited: 55
Intelligent anomaly identification in cyber-physical inverter-based systems
Asad Ali Khan, Omar Ali Beg, Miltiadis Alamaniotis, et al.
Electric Power Systems Research (2021) Vol. 193, pp. 107024-107024
Closed Access | Times Cited: 52
A novel hybrid approach based on variational heteroscedastic Gaussian process regression for multi-step ahead wind speed forecasting
Chu Zhang, Peng Tian, Muhammad Shahzad Nazir
International Journal of Electrical Power & Energy Systems (2021) Vol. 136, pp. 107717-107717
Closed Access | Times Cited: 51
AB-Net: A Novel Deep Learning Assisted Framework for Renewable Energy Generation Forecasting
Noman Khan, Fath U Min Ullah, Ijaz Ul Haq, et al.
Mathematics (2021) Vol. 9, Iss. 19, pp. 2456-2456
Open Access | Times Cited: 46
Optimizing cellulase production from Aspergillus flavus using response surface methodology and machine learning models
Anjali Singhal, Neeta Kumari, Pooja Ghosh, et al.
Environmental Technology & Innovation (2022) Vol. 27, pp. 102805-102805
Open Access | Times Cited: 36
New Insights into the Emerging Trends Research of Machine and Deep Learning Applications in Energy Storage: A Bibliometric Analysis and Publication Trends
Samuel-Soma M. Ajibade, Abdelhamid Zaïdi, Asamh Saleh M. Al Luhayb, et al.
International Journal of Energy Economics and Policy (2023) Vol. 13, Iss. 5, pp. 303-314
Open Access | Times Cited: 22
Prognostics for Lithium-ion batteries for electric Vertical Take-off and Landing aircraft using data-driven machine learning
Mihaela Mitici, Birgitte Hennink, Marilena Pavel, et al.
Energy and AI (2023) Vol. 12, pp. 100233-100233
Open Access | Times Cited: 21
AI-based forecasting for optimised solar energy management and smart grid efficiency
Pierre Bouquet, Ilya Jackson, Mostafa Nick, et al.
International Journal of Production Research (2023) Vol. 62, Iss. 13, pp. 4623-4644
Open Access | Times Cited: 20
Predictive operations of marine pumped hydro-storage towards real time offshore wind-wave power complementarity: An event-triggered MPC approach
Xiuxing Yin, Zhigao Zhao, Weijia Yang
Journal of Energy Storage (2023) Vol. 62, pp. 106583-106583
Closed Access | Times Cited: 19

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