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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:

Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm
W. J. M. Lakmini Prarthana Jayasinghe, Ravinesh C. Deo, Afshin Ghahramani, et al.
IEEE Access (2021) Vol. 9, pp. 166695-166708
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Simulation of forest fire spread based on artificial intelligence
Zechuan Wu, Bin Wang, Mingze Li, et al.
Ecological Indicators (2022) Vol. 136, pp. 108653-108653
Open Access | Times Cited: 89
A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction
Sujan Ghimire, Thong Nguyen‐Huy, Mohanad S. AL‐Musaylh, et al.
Energy (2023) Vol. 275, pp. 127430-127430
Open Access | Times Cited: 43
Probabilistic-based electricity demand forecasting with hybrid convolutional neural network-extreme learning machine model
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107918-107918
Closed Access | Times Cited: 15
A novel wind power prediction approach using multivariate variational mode decomposition and multi-objective crisscross optimization based deep extreme learning machine
Anbo Meng, Zibin Zhu, Weisi Deng, et al.
Energy (2022) Vol. 260, pp. 124957-124957
Closed Access | Times Cited: 42
Combining a deep learning model with multivariate empirical mode decomposition for hourly global horizontal irradiance forecasting
Priya Gupta, Rhythm Singh
Renewable Energy (2023) Vol. 206, pp. 908-927
Closed Access | Times Cited: 29
Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Applied Energy (2023) Vol. 353, pp. 122059-122059
Open Access | Times Cited: 25
An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting
Lizhi Tao, Zhichao Cui, Yufeng He, et al.
The Science of The Total Environment (2024) Vol. 929, pp. 172465-172465
Closed Access | Times Cited: 12
Electricity demand error corrections with attention bi-directional neural networks
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Energy (2024) Vol. 291, pp. 129938-129938
Closed Access | Times Cited: 11
Medical Image Classifications Using Convolutional Neural Networks: A Survey of Current Methods and Statistical Modeling of the Literature
Foziya Ahmed Mohammed, Kula Kekeba Tune, Beakal Gizachew Assefa, et al.
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 1, pp. 699-736
Open Access | Times Cited: 10
A state-of-the-art review of long short-term memory models with applications in hydrology and water resources
Zhong-kai Feng, J. Zhang, Wen-jing Niu
Applied Soft Computing (2024), pp. 112352-112352
Closed Access | Times Cited: 8
A Multi–Step Approach for Optically Active and Inactive Water Quality Parameter Estimation Using Deep Learning and Remote Sensing
Mehreen Ahmed, Rafia Mumtaz, Zahid Anwar, et al.
Water (2022) Vol. 14, Iss. 13, pp. 2112-2112
Open Access | Times Cited: 35
Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Energy Conversion and Management (2023) Vol. 297, pp. 117707-117707
Open Access | Times Cited: 18
Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables
Sujan Ghimire, Thong Nguyen‐Huy, Mohanad S. AL‐Musaylh, et al.
Energy and AI (2023) Vol. 14, pp. 100302-100302
Open Access | Times Cited: 16
Deep Learning Approaches for Water Stress Forecasting in Arboriculture Using Time Series of Remote Sensing Images: Comparative Study between ConvLSTM and CNN-LSTM Models
Ismail Bounoua, Youssef Saidi, Reda Yaagoubi, et al.
Technologies (2024) Vol. 12, Iss. 6, pp. 77-77
Open Access | Times Cited: 7
Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model
Sujan Ghimire, Ravinesh C. Deo, S. Ali Pourmousavi, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108702-108702
Open Access | Times Cited: 6
Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model
Weibing Jia, Yubin Zhang, Zhengying Wei, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0281478-e0281478
Open Access | Times Cited: 13
Estimating aboveground biomass of urban trees based on ICESat-2 LiDAR and Zhuhai-1 hyperspectral data
Chao Wei, Haiming Qin, Jinwen Ji, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024) Vol. 135, pp. 103605-103605
Closed Access | Times Cited: 4
Forecasting hourly day-ahead solar photovoltaic power generation by assembling a new adaptive multivariate data analysis with a long short-term memory network
Priya Gupta, Rhythm Singh
Sustainable Energy Grids and Networks (2023) Vol. 35, pp. 101133-101133
Closed Access | Times Cited: 11
Combining simple and less time complex ML models with multivariate empirical mode decomposition to obtain accurate GHI forecast
Priya Gupta, Rhythm Singh
Energy (2022) Vol. 263, pp. 125844-125844
Closed Access | Times Cited: 17
Multi-Step-Ahead Wind Speed Forecast System: Hybrid Multivariate Decomposition and Feature Selection-Based Gated Additive Tree Ensemble Model
Lionel Joseph, Ravinesh C. Deo, David Casillas-Pérez, et al.
IEEE Access (2024) Vol. 12, pp. 58750-58777
Open Access | Times Cited: 2
Proposal of a methodology for prediction of heavy metals concentration based on PM2.5 concentration and meteorological variables using machine learning
Shin-Young Park, Hye‐Won Lee, Jaymin Kwon, et al.
Asian Journal of Atmospheric Environment (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 1
Multifaceted irradiance prediction by exploiting hybrid decomposition-entropy-Spatiotemporal attention based Sequence2Sequence models
Muhammad Sibtain, Xianshan Li, Snoober Saleem, et al.
Renewable Energy (2022) Vol. 196, pp. 648-682
Closed Access | Times Cited: 7
Assessing Spatial Patterns of Surface Soil Moisture and Vegetation Cover in Batifa, Kurdistan Region-Iraq: Machine Learning Approach
Islam S. Khurshed, Yaseen T. Mustafa, Mohammed A. Fayyadh
IEEE Access (2023) Vol. 11, pp. 130406-130417
Open Access | Times Cited: 3
Modeling Evapotranspiration in IoT based WSN for Irrigation Scheduling: An Optimized DL Approach
Gitika Sharma, Pulkit, Himanshu Sharma, et al.
GLOBECOM 2022 - 2022 IEEE Global Communications Conference (2022), pp. 1948-1953
Closed Access | Times Cited: 4
Prediction of Sea Level Using Double Data Decomposition and Hybrid Deep Learning Model for Northern Territory, Australia
Nawin Raj, J. Ganesh Murali, Lila Singh‐Peterson, et al.
Mathematics (2024) Vol. 12, Iss. 15, pp. 2376-2376
Open Access
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