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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:

A Novel CNN-GRU-Based Hybrid Approach for Short-Term Residential Load Forecasting
Muhammad Sajjad, Zulfiqar Ahmad Khan, Amin Ullah, et al.
IEEE Access (2020) Vol. 8, pp. 143759-143768
Open Access | Times Cited: 378

Showing 1-25 of 378 citing articles:

AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
Yassine Himeur, Mariam Elnour, Fodil Fadli, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 4929-5021
Open Access | Times Cited: 257
Hybrid VMD-CNN-GRU-based model for short-term forecasting of wind power considering spatio-temporal features
Zeni Zhao, Sining Yun, Lingyun Jia, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105982-105982
Closed Access | Times Cited: 148
Building energy prediction using artificial neural networks: A literature survey
Chujie Lu, Sihui Li, Zhengjun Lu
Energy and Buildings (2021) Vol. 262, pp. 111718-111718
Closed Access | Times Cited: 146
Long Short-Term Memory Network-Based Metaheuristic for Effective Electric Energy Consumption Prediction
Simran Kaur Hora, P Rachana, Rocío Pérez de Prado, et al.
Applied Sciences (2021) Vol. 11, Iss. 23, pp. 11263-11263
Open Access | Times Cited: 136
Spatial-Temporal Residential Short-Term Load Forecasting via Graph Neural Networks
Weixuan Lin, Di Wu, Benoît Boulet
IEEE Transactions on Smart Grid (2021) Vol. 12, Iss. 6, pp. 5373-5384
Closed Access | Times Cited: 123
Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand
Charan Sekhar, Ratna Dahiya
Energy (2023) Vol. 268, pp. 126660-126660
Closed Access | Times Cited: 109
Inception inspired CNN-GRU hybrid network for human activity recognition
Nidhi Dua, Shiva Nand Singh, Vijay Bhaskar Semwal, et al.
Multimedia Tools and Applications (2022) Vol. 82, Iss. 4, pp. 5369-5403
Closed Access | Times Cited: 91
BiCuDNNLSTM-1dCNN — A hybrid deep learning-based predictive model for stock price prediction
Anika Kanwal, Man Fai Lau, Sebastian Ng, et al.
Expert Systems with Applications (2022) Vol. 202, pp. 117123-117123
Closed Access | Times Cited: 89
Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting
Samee U. Khan, Noman Khan, Fath U Min Ullah, et al.
Energy and Buildings (2022) Vol. 279, pp. 112705-112705
Closed Access | Times Cited: 81
Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks
Tai-Yu Ma, Sébastien Faye
Energy (2022) Vol. 244, pp. 123217-123217
Open Access | Times Cited: 78
Dual stream network with attention mechanism for photovoltaic power forecasting
Zulfiqar Ahmad Khan, Tanveer Hussain, Sung Wook Baik
Applied Energy (2023) Vol. 338, pp. 120916-120916
Closed Access | Times Cited: 69
Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead
Saima Akhtar, Sulman Shahzad, Asad Zaheer, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4060-4060
Open Access | Times Cited: 49
Hybrid WT–CNN–GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features
Mohammad Zamani, Mohammad Reza Nikoo, Ghazi Al-Rawas, et al.
Journal of Environmental Management (2024) Vol. 358, pp. 120756-120756
Closed Access | Times Cited: 21
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
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
Intelligent deep learning techniques for energy consumption forecasting in smart buildings: a review
R. Mathumitha, P. Rathika, K. Manimala
Artificial Intelligence Review (2024) Vol. 57, Iss. 2
Open Access | Times Cited: 14
DB-Net: A novel dilated CNN based multi-step forecasting model for power consumption in integrated local energy systems
Noman Khan, Ijaz Ul Haq, Samee U. Khan, et al.
International Journal of Electrical Power & Energy Systems (2021) Vol. 133, pp. 107023-107023
Closed Access | Times Cited: 99
Multi-dimensional prediction method based on Bi-LSTMC for ship roll
Yuchao Wang, Hui Wang, Bin Zhou, et al.
Ocean Engineering (2021) Vol. 242, pp. 110106-110106
Closed Access | Times Cited: 91
Short-Term Energy Consumption Forecasting at the Edge: A Federated Learning Approach
Marco Savi, Fabrizio Olivadese
IEEE Access (2021) Vol. 9, pp. 95949-95969
Open Access | Times Cited: 90
Multi-Model Fusion Short-Term Load Forecasting Based on Random Forest Feature Selection and Hybrid Neural Network
Xuan Yi, Weiguo Si, Jiong Zhu, et al.
IEEE Access (2021) Vol. 9, pp. 69002-69009
Open Access | Times Cited: 85
Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model
Dabeeruddin Syed, Haitham Abu‐Rub, Ali Ghrayeb, et al.
IEEE Access (2021) Vol. 9, pp. 33498-33511
Open Access | Times Cited: 80
Probabilistic Solar Irradiation Forecasting Based on Variational Bayesian Inference With Secure Federated Learning
Xiaoning Zhang, Fang Fang, Jiaqi Wang
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 11, pp. 7849-7859
Closed Access | Times Cited: 75
Electrical Energy Prediction in Residential Buildings for Short-Term Horizons Using Hybrid Deep Learning Strategy
Zulfiqar Ahmad Khan, Amin Ullah, Waseem Ullah, et al.
Applied Sciences (2020) Vol. 10, Iss. 23, pp. 8634-8634
Open Access | Times Cited: 74
Federated learning with hyperparameter-based clustering for electrical load forecasting
Nastaran Gholizadeh, Petr Musı́lek
Internet of Things (2021) Vol. 17, pp. 100470-100470
Open Access | Times Cited: 65
Short-Term Energy Forecasting Framework Using an Ensemble Deep Learning Approach
Mustaqeem Mustaqeem, Muhammad Ishaq, Soonil Kwon
IEEE Access (2021) Vol. 9, pp. 94262-94271
Open Access | Times Cited: 63
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