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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:

Empirical Mode Decomposition Based Deep Learning for Electricity Demand Forecasting
Jatin Bedi, Durga Toshniwal
IEEE Access (2018) Vol. 6, pp. 49144-49156
Open Access | Times Cited: 173

Showing 1-25 of 173 citing articles:

A deep learning framework for building energy consumption forecast
Nivethitha Somu, M. R. Gauthama Raman, Krithi Ramamritham
Renewable and Sustainable Energy Reviews (2020) Vol. 137, pp. 110591-110591
Closed Access | Times Cited: 334
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
Abdullah Al Mamun, Md. Sohel, Naeem Mohammad, et al.
IEEE Access (2020) Vol. 8, pp. 134911-134939
Open Access | Times Cited: 254
Driven by Data or Derived Through Physics? A Review of Hybrid Physics Guided Machine Learning Techniques With Cyber-Physical System (CPS) Focus
Rahul Rai, Chandan K. Sahu
IEEE Access (2020) Vol. 8, pp. 71050-71073
Open Access | Times Cited: 216
A Hybrid Residual Dilated LSTM and Exponential Smoothing Model for Midterm Electric Load Forecasting
Grzegorz Dudek, Paweł Pełka, Slawek Smyl
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 7, pp. 2879-2891
Open Access | Times Cited: 148
Load Forecasting Techniques for Power System: Research Challenges and Survey
Naqash Ahmad, Yazeed Yasin Ghadi, Muhammad Adnan, et al.
IEEE Access (2022) Vol. 10, pp. 71054-71090
Open Access | Times Cited: 133
Highly accurate peak and valley prediction short-term net load forecasting approach based on decomposition for power systems with high PV penetration
Osaka Rubasinghe, Tingze Zhang, Xinan Zhang, et al.
Applied Energy (2023) Vol. 333, pp. 120641-120641
Open Access | Times Cited: 48
Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection
Xin Gao, Xiaobing Li, Bing Zhao, et al.
Energies (2019) Vol. 12, Iss. 6, pp. 1140-1140
Open Access | Times Cited: 121
Deep learning in electrical utility industry: A comprehensive review of a decade of research
Manohar Mishra, Janmenjoy Nayak, Bighnaraj Naik, et al.
Engineering Applications of Artificial Intelligence (2020) Vol. 96, pp. 104000-104000
Closed Access | Times Cited: 94
Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model
Xue‐Bo Jin, Nian-Xiang Yang, Xiaoyi Wang, et al.
Sensors (2020) Vol. 20, Iss. 5, pp. 1334-1334
Open Access | Times Cited: 93
Real-Time Stochastic Optimization of Energy Storage Management Using Deep Learning-Based Forecasts for Residential PV Applications
Faeza Hafiz, M A Awal, Anderson Rodrigo de Queiroz, et al.
IEEE Transactions on Industry Applications (2020) Vol. 56, Iss. 3, pp. 2216-2226
Open Access | Times Cited: 91
A novel hybrid model based on STL decomposition and one-dimensional convolutional neural networks with positional encoding for significant wave height forecast
Shaobo Yang, Zegui Deng, Xingfei Li, et al.
Renewable Energy (2021) Vol. 173, pp. 531-543
Open Access | Times Cited: 85
Deep Hybrid Model Based on EMD with Classification by Frequency Characteristics for Long-Term Air Quality Prediction
Xue‐Bo Jin, Nian-Xiang Yang, Xiaoyi Wang, et al.
Mathematics (2020) Vol. 8, Iss. 2, pp. 214-214
Open Access | Times Cited: 82
Energy load time-series forecast using decomposition and autoencoder integrated memory network
Jatin Bedi, Durga Toshniwal
Applied Soft Computing (2020) Vol. 93, pp. 106390-106390
Closed Access | Times Cited: 76
Genetic-Algorithm-Optimized Sequential Model for Water Temperature Prediction
Stephen Stajkowski, Deepak Kumar, Pijush Samui, et al.
Sustainability (2020) Vol. 12, Iss. 13, pp. 5374-5374
Open Access | Times Cited: 73
Air quality forecasting with hybrid LSTM and extended stationary wavelet transform
Yongkang Zeng, Jingjing Chen, Ning Jin, et al.
Building and Environment (2022) Vol. 213, pp. 108822-108822
Open Access | Times Cited: 63
The Impact of Digital Transformation on Environmental Sustainability
Thanh Cong Truong
Advances in Multimedia (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 40
AI-Empowered Methods for Smart Energy Consumption: A Review of Load Forecasting, Anomaly Detection and Demand Response
Xinlin Wang, Hao Wang, Binayak Bhandari, et al.
International Journal of Precision Engineering and Manufacturing-Green Technology (2023) Vol. 11, Iss. 3, pp. 963-993
Open Access | Times Cited: 39
A novel hybrid model for six main pollutant concentrations forecasting based on improved LSTM neural networks
Shenyi Xu, Wei Li, Yuhan Zhu, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 38
Current status, challenges, and prospects of data-driven urban energy modeling: A review of machine learning methods
Prajowal Manandhar, Hasan Rafiq, Edwin Rodríguez-Ubiñas
Energy Reports (2023) Vol. 9, pp. 2757-2776
Open Access | Times Cited: 30
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
Hybrid short-term load forecasting using CGAN with CNN and semi-supervised regression
Xiangya Bu, Qiuwei Wu, Bin Zhou, et al.
Applied Energy (2023) Vol. 338, pp. 120920-120920
Closed Access | Times Cited: 29
Improving the accuracy of multi-step prediction of building energy consumption based on EEMD-PSO-Informer and long-time series
Feiyu Li, Zhibo Wan, Thomas Koch, et al.
Computers & Electrical Engineering (2023) Vol. 110, pp. 108845-108845
Closed Access | Times Cited: 24
A framework for electricity load forecasting based on attention mechanism time series depthwise separable convolutional neural network
Huifeng Xu, Feihu Hu, Xinhao Liang, et al.
Energy (2024) Vol. 299, pp. 131258-131258
Closed Access | Times Cited: 13
Forecasting smart home electricity consumption using VMD-Bi-GRU
Ismael Jrhilifa, Hamid Ouadi, Abdelilah Jilbab, et al.
Energy Efficiency (2024) Vol. 17, Iss. 4
Closed Access | Times Cited: 12
A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems
Kinza Fida, Usman Abbasi, Muhammad Adnan, et al.
Results in Engineering (2024) Vol. 23, pp. 102773-102773
Open Access | Times Cited: 8
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