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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 Based PV Power Generation Forecasting in Alice Springs
Khizir Mahmud, Sami Azam, Asif Karim, et al.
IEEE Access (2021) Vol. 9, pp. 46117-46128
Open Access | Times Cited: 108

Showing 1-25 of 108 citing articles:

TimeDistributed-CNN-LSTM: A Hybrid Approach Combining CNN and LSTM to Classify Brain Tumor on 3D MRI Scans Performing Ablation Study
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, et al.
IEEE Access (2022) Vol. 10, pp. 60039-60059
Open Access | Times Cited: 96
Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects
Natei Ermias Benti, Mesfin Diro Chaka, Addisu Gezahegn Semie
Sustainability (2023) Vol. 15, Iss. 9, pp. 7087-7087
Open Access | Times Cited: 83
The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
Seyed Matin Malakouti, Mohammad Bagher Menhaj, Amir Abolfazl Suratgar
Cleaner Engineering and Technology (2023) Vol. 15, pp. 100664-100664
Open Access | Times Cited: 76
Short-term PV power forecasting using variational mode decomposition integrated with Ant colony optimization and neural network
Solomon Netsanet, Dehua Zheng, Wei Zhang, et al.
Energy Reports (2022) Vol. 8, pp. 2022-2035
Open Access | Times Cited: 73
Multi-timescale photovoltaic power forecasting using an improved Stacking ensemble algorithm based LSTM-Informer model
Yisheng Cao, Gang Liu, Dong–Hua Luo, et al.
Energy (2023) Vol. 283, pp. 128669-128669
Closed Access | Times Cited: 63
A cohesive structure of Bi-directional long-short-term memory (BiLSTM) -GRU for predicting hourly solar radiation
Neethu Elizabeth Michael, Ramesh C. Bansal, Ali Ahmed Adam Ismail, et al.
Renewable Energy (2024) Vol. 222, pp. 119943-119943
Closed Access | Times Cited: 17
Enhancing PV power forecasting with deep learning and optimizing solar PV project performance with economic viability: A multi-case analysis of 10 MW Masdar project in UAE
Muhammad Faizan Tahir, Anthony Tzes, Muhammad Zain Yousaf
Energy Conversion and Management (2024) Vol. 311, pp. 118549-118549
Closed Access | Times Cited: 17
A short-term forecasting method for photovoltaic power generation based on the TCN-ECANet-GRU hybrid model
Xiuli Xiang, Xingyu Li, Yaoli Zhang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 15
Forecasting Solar Energy Production Using Machine Learning
C. Vennila, Anita Titus, T. Sri Sudha, et al.
International Journal of Photoenergy (2022) Vol. 2022, pp. 1-7
Open Access | Times Cited: 61
Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints
Yuan‐Kang Wu, Cheng‐Liang Huang, Quoc‐Thang Phan, et al.
Energies (2022) Vol. 15, Iss. 9, pp. 3320-3320
Open Access | Times Cited: 58
Hybrid ultra-short-term PV power forecasting system for deterministic forecasting and uncertainty analysis
Jianzhou Wang, Yue Yu, Bo Zeng, et al.
Energy (2023) Vol. 288, pp. 129898-129898
Closed Access | Times Cited: 24
A Review for Green Energy Machine Learning and AI Services
Yukta Mehta, Rui Xu, Benjamin Lim, et al.
Energies (2023) Vol. 16, Iss. 15, pp. 5718-5718
Open Access | Times Cited: 22
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
A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches
Andreea Săbăduş, Robert Blaga, Sergiu-Mihai Hategan, et al.
Renewable Energy (2024) Vol. 226, pp. 120385-120385
Closed Access | Times Cited: 13
Vulnerability of Machine Learning Approaches Applied in IoT-Based Smart Grid: A Review
Zhenyong Zhang, Mengxiang Liu, Mingyang Sun, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 11, pp. 18951-18975
Open Access | Times Cited: 12
A hybrid machine-learning model for solar irradiance forecasting
Ameera M Almarzooqi, Maher Maalouf, Tarek H. M. EL-Fouly, et al.
Clean Energy (2024) Vol. 8, Iss. 1, pp. 100-110
Open Access | Times Cited: 12
Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework
Sameer Al‐Dahidi, Manoharan Madhiarasan, Loiy Al‐Ghussain, et al.
Energies (2024) Vol. 17, Iss. 16, pp. 4145-4145
Open Access | Times Cited: 11
Latest Advancements in Solar Photovoltaic-Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses
Hisham Alghamdi, Chika Maduabuchi, Kingsley Okoli, et al.
International Journal of Energy Research (2024) Vol. 2024, pp. 1-29
Open Access | Times Cited: 10
Stabilization of Expansive Clays with Basalt Fibers and Prediction of Strength by Machine Learning
Sedat Sert, Eylem Arslan, Pınar Ocakbaşı, et al.
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 10, pp. 13651-13670
Open Access | Times Cited: 9
Resiliency of forecasting methods in different application areas of smart grids: A review and future prospects
M. A. Rahman, Md. Rashidul Islam, Md. Alamgir Hossain, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108785-108785
Closed Access | Times Cited: 8
Implementation of Deep Learning Methods to Identify Rotten Fruits
Sovon Chakraborty, F. M. Javed Mehedi Shamrat, Md. Masum Billah, et al.
2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (2021), pp. 1207-1212
Closed Access | Times Cited: 54
A Performance Based Study on Deep Learning Algorithms in the Effective Prediction of Breast Cancer
Pronab Ghosh, Sami Azam, Khan Md. Hasib, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-8
Closed Access | Times Cited: 53
Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Mohamed Massaoudi, Inès Chihi, Haitham Abu‐Rub, et al.
IEEE Access (2021) Vol. 9, pp. 136593-136615
Open Access | Times Cited: 50
A Review of Machine Learning-Based Photovoltaic Output Power Forecasting: Nordic Context
Berhane Darsene Dimd, Steve Völler, Ümit Cali, et al.
IEEE Access (2022) Vol. 10, pp. 26404-26425
Open Access | Times Cited: 36
Solar Radiation Forecasting Using Machine Learning and Ensemble Feature Selection
Edna S. Solano, Payman Dehghanian, Carolina M. Affonso
Energies (2022) Vol. 15, Iss. 19, pp. 7049-7049
Open Access | Times Cited: 34
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