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Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Numero 3 (June 2023)
Accesso libero
An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
Tacjana Niksa-Rynkiewicz
Tacjana Niksa-Rynkiewicz
,
Piotr Stomma
Piotr Stomma
,
Anna Witkowska
Anna Witkowska
,
Danuta Rutkowska
Danuta Rutkowska
,
Adam Słowik
Adam Słowik
,
Krzysztof Cpałka
Krzysztof Cpałka
,
Joanna Jaworek-Korjakowska
Joanna Jaworek-Korjakowska
e
Piotr Kolendo
Piotr Kolendo
| 23 giu 2023
Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Numero 3 (June 2023)
INFORMAZIONI SU QUESTO ARTICOLO
Articolo precedente
Articolo Successivo
Sommario
Bibliografia
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CONDIVIDI
Pubblicato online:
23 giu 2023
Pagine:
197 - 210
Ricevuto:
26 mag 2023
Accettato:
27 mag 2023
DOI:
https://doi.org/10.2478/jaiscr-2023-0015
Parole chiave
Renewable Energy
,
Wind Energy
,
Wind Power
,
Wind Turbine
,
Short-Term Wind Power Prediction
,
Deep Learning
,
Convolutional Neural Networks
,
Gated Recurrent Unit
,
Hierarchical Multilayer Perceptron
,
Deep Neural Networks
© 2023 Tacjana Niksa-Rynkiewicz et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Tacjana Niksa-Rynkiewicz
Gdańsk University of Technology, Faculty of Ocean Engineering and Ship Technology
Gdańsk, Poland
Piotr Stomma
University of Białystok, Institute of Computer Science
Białystok, Poland
Anna Witkowska
Gdańsk University of Technology, Faculty of Electrical and Control Engineering
Gdańsk, Poland
Danuta Rutkowska
University of Social Sciences, Information Technology Institute
Łódź, Poland
Adam Słowik
Koszalin University of Technology, Department of Electronics and Computer Science
Koszalin, Poland
Krzysztof Cpałka
Częstochowa University of Technology, Department of Intelligent Computer Systems
Częstochowa, Poland
Joanna Jaworek-Korjakowska
AGH University, Department of Automatic Control and Robotics, Center of Excellence in Artificial Intelligence
Kraków, Poland
Piotr Kolendo
Institute of Power Engineering Department of Power Automation
Gdańsk, Poland