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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:

An optimized model using LSTM network for demand forecasting
Hossein Abbasimehr, Mostafa Shabani, Mohsen Yousefi
Computers & Industrial Engineering (2020) Vol. 143, pp. 106435-106435
Closed Access | Times Cited: 389

Showing 1-25 of 389 citing articles:

Prediction and analysis of COVID-19 positive cases using deep learning models: A descriptive case study of India
Parul Arora, Himanshu Kumar, Bijaya Ketan Panigrahi
Chaos Solitons & Fractals (2020) Vol. 139, pp. 110017-110017
Open Access | Times Cited: 345
Residential load forecasting based on LSTM fusing self-attention mechanism with pooling
Haixiang Zang, Ruiqi Xu, Lilin Cheng, et al.
Energy (2021) Vol. 229, pp. 120682-120682
Closed Access | Times Cited: 176
Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization
Hossein Abbasimehr, Reza Paki
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110511-110511
Open Access | Times Cited: 159
Improving time series forecasting using LSTM and attention models
Hossein Abbasimehr, Reza Paki
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 13, Iss. 1, pp. 673-691
Closed Access | Times Cited: 158
NILM applications: Literature review of learning approaches, recent developments and challenges
Georgios-Fotios Angelis, Christos Timplalexis, Stelios Krinidis, et al.
Energy and Buildings (2022) Vol. 261, pp. 111951-111951
Closed Access | Times Cited: 119
Short-Term Electricity Load Forecasting with Machine Learning
Ernesto Aguilar Madrid, Nuno António
Information (2021) Vol. 12, Iss. 2, pp. 50-50
Open Access | Times Cited: 110
A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India
Shobhit Chaturvedi, E. Rajasekar, Sukumar Natarajan, et al.
Energy Policy (2022) Vol. 168, pp. 113097-113097
Closed Access | Times Cited: 100
Interval forecasting for urban water demand using PSO optimized KDE distribution and LSTM neural networks
Baigang Du, Shuo Huang, Jun Guo, et al.
Applied Soft Computing (2022) Vol. 122, pp. 108875-108875
Closed Access | Times Cited: 98
A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection
Hosein Fanai, Hossein Abbasimehr
Expert Systems with Applications (2023) Vol. 217, pp. 119562-119562
Closed Access | Times Cited: 87
Deep transfer learning approaches for Monkeypox disease diagnosis
Md Manjurul Ahsan, Muhammad Ramiz Uddin, Md Shahin Ali, et al.
Expert Systems with Applications (2023) Vol. 216, pp. 119483-119483
Open Access | Times Cited: 84
Predictive Analytics for Demand Forecasting – A Comparison of SARIMA and LSTM in Retail SCM
Taha Falatouri, Farzaneh Darbanian, Patrick Brandtner, et al.
Procedia Computer Science (2022) Vol. 200, pp. 993-1003
Open Access | Times Cited: 79
Neural networks based multivariate time series forecasting of solar radiation using meteorological data of different cities of Bangladesh
Abrar Faisal, Afikur Rahman, Mohammad Tanvir Mahmud Habib, et al.
Results in Engineering (2022) Vol. 13, pp. 100365-100365
Open Access | Times Cited: 76
A new convolutional dual-channel Transformer network with time window concatenation for remaining useful life prediction of rolling bearings
Li Jiang, Tianao Zhang, Lei Wei, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101966-101966
Closed Access | Times Cited: 55
A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China
Hanxiao Shi, Anlei Wei, Xiaozhen Xu, et al.
Journal of Environmental Management (2024) Vol. 352, pp. 120131-120131
Closed Access | Times Cited: 52
Applications of Artificial Intelligence in Inventory Management: A Systematic Review of the Literature
Özge Albayrak Ünal, Burak Erkayman, Bilal Usanmaz
Archives of Computational Methods in Engineering (2023)
Closed Access | Times Cited: 44
MACHINE LEARNING'S INFLUENCE ON SUPPLY CHAIN AND LOGISTICS OPTIMIZATION IN THE OIL AND GAS SECTOR: A COMPREHENSIVE ANALYSIS
Agnes Clare Odimarha, Sodrudeen Abolore Ayodeji, Emmanuel Adeyemi Abaku
Computer Science & IT Research Journal (2024) Vol. 5, Iss. 3, pp. 725-740
Open Access | Times Cited: 42
Forecasting seasonal demand for retail: A Fourier time-varying grey model
Lili Ye, Naiming Xie, John E. Boylan, et al.
International Journal of Forecasting (2024) Vol. 40, Iss. 4, pp. 1467-1485
Closed Access | Times Cited: 19
Short-Term Load Forecasting Using Channel and Temporal Attention Based Temporal Convolutional Network
Xianlun Tang, Hongxu Chen, Wenhao Xiang, et al.
Electric Power Systems Research (2021) Vol. 205, pp. 107761-107761
Closed Access | Times Cited: 97
Design of experiments using artificial neural network ensemble for photovoltaic generation forecasting
Max Olinto Moreira, Pedro Paulo Balestrassi, Anderson Paulo de Paiva, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 135, pp. 110450-110450
Closed Access | Times Cited: 87
An end-to-end framework for remaining useful life prediction of rolling bearing based on feature pre-extraction mechanism and deep adaptive transformer model
Xuanyuan Su, Hongmei Liu, Laifa Tao, et al.
Computers & Industrial Engineering (2021) Vol. 161, pp. 107531-107531
Closed Access | Times Cited: 77
The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality
Guo Liang, Weiguo Fang, Qiuhong Zhao, et al.
Computers & Industrial Engineering (2021) Vol. 161, pp. 107598-107598
Closed Access | Times Cited: 73
Time-series prediction of shield movement performance during tunneling based on hybrid model
Song-Shun Lin, Ning Zhang, Annan Zhou, et al.
Tunnelling and Underground Space Technology (2021) Vol. 119, pp. 104245-104245
Closed Access | Times Cited: 62
Probabilistic estimation of flexural loading capacity of existing RC structures based on observational corrosion-induced crack width distribution using machine learning
Mingyang Zhang, Mitsuyoshi Akiyama, Mina Shintani, et al.
Structural Safety (2021) Vol. 91, pp. 102098-102098
Open Access | Times Cited: 58
A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting
Hossein Abbasimehr, Reza Paki, Aram Bahrini
Neural Computing and Applications (2021) Vol. 34, Iss. 4, pp. 3135-3149
Open Access | Times Cited: 57
Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models
Nemesio Fava Sopelsa Neto, Stéfano Frizzo Stefenon, Luiz Henrique Meyer, et al.
Sensors (2022) Vol. 22, Iss. 16, pp. 6121-6121
Open Access | Times Cited: 54
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