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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:

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features
Lechen Li, Christoph J. Meinrenken, Vijay Modi, et al.
Applied Energy (2021) Vol. 287, pp. 116509-116509
Open Access | Times Cited: 70

Showing 26-50 of 70 citing articles:

Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review
Filipe Rodrigues, Carlos Cardeira, J. M. F. Calado, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4098-4098
Open Access | Times Cited: 8
Memory-based Transformer with shorter window and longer horizon for multivariate time series forecasting
Liu Yang, Zheng Wang, Xinyang Yu, et al.
Pattern Recognition Letters (2022) Vol. 160, pp. 26-33
Closed Access | Times Cited: 13
Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review
F. Martins Rodrigues, Carlos Cardeira, J. M. F. Calado, et al.
(2023)
Open Access | Times Cited: 7
A novel cluster based multi-index nonlinear ensemble framework for carbon price forecasting
Jujie Wang, Zhenzhen Zhuang
Environment Development and Sustainability (2022) Vol. 25, Iss. 7, pp. 6225-6247
Closed Access | Times Cited: 12
Energy Consumption Forecasting for Smart Meters Using Extreme Learning Machine Ensemble
Paulo S. G. de Mattos Neto, João Fausto Lorenzato de Oliveira, Priscilla Bassetto, et al.
Sensors (2021) Vol. 21, Iss. 23, pp. 8096-8096
Open Access | Times Cited: 15
Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method
Muhammad Irfan, Ali Raza, Faisal Althobiani, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2022) Vol. 72, Iss. 3, pp. 4249-4265
Open Access | Times Cited: 10
Short-Term Electricity Load Forecasting Using a New Intelligence-Based Application
Salahuddin Khan
Sustainability (2023) Vol. 15, Iss. 16, pp. 12311-12311
Open Access | Times Cited: 6
TDG4MSF: A temporal decomposition enhanced graph neural network for multivariate time series forecasting
Hao Miao, Yilin Zhang, Zefei Ning, et al.
Applied Intelligence (2023) Vol. 53, Iss. 23, pp. 28254-28267
Closed Access | Times Cited: 6
Weather classification-based load and solar insolation forecasting for residential applications with LSTM neural networks
Dipanshu Naware, Arghya Mitra
Electrical Engineering (2021) Vol. 104, Iss. 1, pp. 347-361
Closed Access | Times Cited: 14
A Calculation Model of Carbon Emissions Based on Multi-Scenario Simulation Analysis of Electricity Consumption
Xiaoli Chen, Zhiwei Liao, Zhihua Gao, et al.
Sustainability (2022) Vol. 14, Iss. 14, pp. 8765-8765
Open Access | Times Cited: 9
A residential load forecasting method for multi-attribute adversarial learning considering multi-source uncertainties
Yongxin Su, Qiyao He, Jie Chen, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 154, pp. 109421-109421
Open Access | Times Cited: 5
Privacy-preserving household load forecasting based on non-intrusive load monitoring: A federated deep learning approach
Xinxin Zhou, Jingru Feng, Jian Wang, et al.
PeerJ Computer Science (2022) Vol. 8, pp. e1049-e1049
Open Access | Times Cited: 8
Data-driven Technology Applications in Planning, Demand-side Management, and Cybersecurity for Smart Household Community
Dipanshu Naware, Arghya Mitra
IEEE Transactions on Artificial Intelligence (2024) Vol. 5, Iss. 10, pp. 4868-4883
Closed Access | Times Cited: 1
Multi-area short-term load forecasting based on spatiotemporal graph neural network
Yunlong Lv, Li Wang, Dunhua Long, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109398-109398
Closed Access | Times Cited: 1
The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market
Vasileios Laitsos, Georgios Vontzos, Paschalis Paraschoudis, et al.
Energies (2024) Vol. 17, Iss. 22, pp. 5797-5797
Open Access | Times Cited: 1
Load profile mining using directed weighted graphs with application towards demand response management
Kakuli Mishra, Srinka Basu, Ujjwal Maulik
Applied Energy (2022) Vol. 311, pp. 118578-118578
Closed Access | Times Cited: 7
A PCA-based variable ranking and selection approach for electric energy load forecasting
Francisco Elânio Bezerra, Flávio Grassi, Cleber Gustavo Dias, et al.
International Journal of Energy Sector Management (2022) Vol. 16, Iss. 6, pp. 1172-1191
Closed Access | Times Cited: 7
Short-term electricity consumption forecasting method based on empirical mode decomposition of long-short term memory network
Bin Yuan, Biao He, Jiang Yan, et al.
IOP Conference Series Earth and Environmental Science (2022) Vol. 983, Iss. 1, pp. 012004-012004
Open Access | Times Cited: 7
Multiscale convolutional recurrent neural network for residential building electricity consumption prediction
Hongxia Wang, Wubin Ma, Zhiru Wang, et al.
Journal of Intelligent & Fuzzy Systems (2022) Vol. 43, Iss. 3, pp. 3479-3491
Open Access | Times Cited: 6
An Experimental Machine Learning Approach for Mid-Term Energy Demand Forecasting
Shu‐Rong Yan, Man‐Wen Tian, Khalid A. Alattas, et al.
IEEE Access (2022) Vol. 10, pp. 118926-118940
Open Access | Times Cited: 6
A novel similar-day based probability density forecasting framework for residential loads
Minghui Cao, Jiang‐Wen Xiao, Hongliang Fang, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 152, pp. 109253-109253
Open Access | Times Cited: 3
Smart Home Energy Management: Sequence-to-Sequence Load Forecasting and Q-Learning
Mina Razghandi, Hao Zhou, Melike Erol‐Kantarci, et al.
2015 IEEE Global Communications Conference (GLOBECOM) (2021), pp. 01-06
Open Access | Times Cited: 7
A New CIGWO-Elman Hybrid Model for Power Load Forecasting
Jie Hao, Changsheng Zhu, Xiuting Guo
Journal of Electrical Engineering and Technology (2021) Vol. 17, Iss. 2, pp. 1319-1333
Closed Access | Times Cited: 7
An adaptive ensemble framework with representative subset based weight correction for short-term forecast of peak power load
Jinxing Che, Yuan Fang, Suling Zhu, et al.
Applied Energy (2022) Vol. 328, pp. 120156-120156
Closed Access | Times Cited: 4
A global forecasting method of heterogeneous household short-term load based on pre-trained autoencoder and deep-LSTM model
Wenhui Zhao, Tong Li, Danyang Xu, et al.
Annals of Operations Research (2022) Vol. 339, Iss. 1-2, pp. 227-259
Closed Access | Times Cited: 4

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