Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Feature selection in machine learning prediction systems for renewable energy applications
Sancho Salcedo‐Sanz, L. Cornejo-Bueno, Luís Prieto, et al.
Renewable and Sustainable Energy Reviews (2018) Vol. 90, pp. 728-741
Closed Access | Times Cited: 150

Showing 1-25 of 150 citing articles:

A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes
Yuchen Jiang, Shen Yin, Jingwei Dong, et al.
IEEE Sensors Journal (2020) Vol. 21, Iss. 11, pp. 12868-12881
Closed Access | Times Cited: 424
Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology
Yun Wang, Bongjin Seo, Bowen Wang, et al.
Energy and AI (2020) Vol. 1, pp. 100014-100014
Open Access | Times Cited: 355
Assessment of deep recurrent neural network-based strategies for short-term building energy predictions
Cheng Fan, Jiayuan Wang, Wenjie Gang, et al.
Applied Energy (2018) Vol. 236, pp. 700-710
Closed Access | Times Cited: 297
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: 294
Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning
Jie Li, Lanjia Pan, Manu Suvarna, et al.
Applied Energy (2020) Vol. 269, pp. 115166-115166
Closed Access | Times Cited: 207
A Survey of Machine Learning Models in Renewable Energy Predictions
Jung-Pin Lai, Yu-Ming Chang, Chieh-Huang Chen, et al.
Applied Sciences (2020) Vol. 10, Iss. 17, pp. 5975-5975
Open Access | Times Cited: 155
Random forest solar power forecast based on classification optimization
Da Liu, Kun Sun
Energy (2019) Vol. 187, pp. 115940-115940
Closed Access | Times Cited: 149
Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms
Mostafa Riazi, Khabat Khosravi, Kaka Shahedi, et al.
The Science of The Total Environment (2023) Vol. 871, pp. 162066-162066
Closed Access | Times Cited: 48
Dynamic NOX emission concentration prediction based on the combined feature selection algorithm and deep neural network
Zhenhao Tang, Shikui Wang, Yue Li
Energy (2024) Vol. 292, pp. 130608-130608
Closed Access | Times Cited: 24
Neural network-based surrogate modeling and optimization of a multigeneration system
Parviz Ghafariasl, Alireza Mahmoudan, Mahmoud Mohammadi, et al.
Applied Energy (2024) Vol. 364, pp. 123130-123130
Open Access | Times Cited: 18
Multi-step ahead wind speed prediction based on optimal feature extraction, long short term memory neural network and error correction strategy
Jujie Wang, Yaning Li
Applied Energy (2018) Vol. 230, pp. 429-443
Closed Access | Times Cited: 129
A holistic review on energy forecasting using big data and deep learning models
Jayanthi Devaraj, Rajvikram Madurai Elavarasan, GM Shafiullah, et al.
International Journal of Energy Research (2021) Vol. 45, Iss. 9, pp. 13489-13530
Open Access | Times Cited: 80
A deep learning based hybrid method for hourly solar radiation forecasting
Chun Sing Lai, Cankun Zhong, Keda Pan, et al.
Expert Systems with Applications (2021) Vol. 177, pp. 114941-114941
Closed Access | Times Cited: 67
Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Applied Energy (2022) Vol. 316, pp. 119063-119063
Closed Access | Times Cited: 67
Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model
Sujan Ghimire, Thong Nguyen‐Huy, Ravinesh C. Deo, et al.
Sustainable materials and technologies (2022) Vol. 32, pp. e00429-e00429
Closed Access | Times Cited: 66
Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia
Sujan Ghimire, Binayak Bhandari, David Casillas-Pérez, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 112, pp. 104860-104860
Open Access | Times Cited: 65
Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Measurement (2022) Vol. 202, pp. 111759-111759
Open Access | Times Cited: 64
Advances of machine learning in multi-energy district communities‒ mechanisms, applications and perspectives
Yuekuan Zhou
Energy and AI (2022) Vol. 10, pp. 100187-100187
Open Access | Times Cited: 62
Artificial Intelligence Based Hybrid Forecasting Approaches for Wind Power Generation: Progress, Challenges and Prospects
Molla Shahadat Hossain Lipu, Md. Sazal Miah, M. A. Hannan, et al.
IEEE Access (2021) Vol. 9, pp. 102460-102489
Open Access | Times Cited: 61
Randomization-based machine learning in renewable energy prediction problems: Critical literature review, new results and perspectives
Javier Del Ser, David Casillas-Pérez, L. Cornejo-Bueno, et al.
Applied Soft Computing (2022) Vol. 118, pp. 108526-108526
Open Access | Times Cited: 50
Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction
Sujan Ghimire, Thong Nguyen‐Huy, Ramendra Prasad, et al.
Cognitive Computation (2022) Vol. 15, Iss. 2, pp. 645-671
Closed Access | Times Cited: 46
Development of a Machine learning assessment method for renewable energy investment decision making
Milad Izanloo, Alireza Aslani, Rahim Zahedi
Applied Energy (2022) Vol. 327, pp. 120096-120096
Closed Access | Times Cited: 40
Wind speed interval prediction based on multidimensional time series of Convolutional Neural Networks
Jiyang Wang, Zhiwu Li
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105987-105987
Closed Access | Times Cited: 38
A survey of artificial intelligence methods for renewable energy forecasting: Methodologies and insights
Blessing Olatunde Abisoye, Yanxia Sun, Zenghui Wang
Renewable energy focus (2023) Vol. 48, pp. 100529-100529
Open Access | Times Cited: 27
Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Sancho Salcedo‐Sanz, Jorge Pérez‐Aracil, Guido Ascenso, et al.
Theoretical and Applied Climatology (2023) Vol. 155, Iss. 1, pp. 1-44
Open Access | Times Cited: 26
Page 1 - Next Page

Scroll to top