| ID | 118680 |
| Author |
Sari, Anggraini Puspita
Tokushima University|University of Merdeka Malang
Kitajima, Takahiro
Tokushima University
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Yasuno, Takashi
Tokushima University
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Prasetya, Dwi Arman
University of Merdeka Malang
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| Keywords | Feed-forward
Backpropagation
Neural network
Wind speed
Wind direction
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| Content Type |
Journal Article
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| Description | This paper presents the prediction system of wind speed and direction using a feed-forward backpropagation neural network (FFBPNN). The input of the prediction system is wind speed and direction which are numerical data and provided by Automated Meteorological Data Acquisition System (AMeDAS) in Japan. The performances of the proposed system is evaluated based on mean square error (MSE) between predicted and observed data. In this paper, we substantiate the usefulness of the proposed prediction system improving prediction accuracy compared to four prediction models.
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| Journal Title |
Journal of Electrical Engineering, Mechatronic and Computer Science
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| ISSN | 26144859
26144867
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| Publisher | University of Merdeka Malang
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| Volume | 3
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| Issue | 1
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| Start Page | 1
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| End Page | 10
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| Published Date | 2020-02
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| Rights | JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. (https://creativecommons.org/licenses/by-nc-sa/4.0/)
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| EDB ID | |
| DOI (Published Version) | |
| URL ( Publisher's Version ) | |
| FullText File | |
| language |
eng
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| TextVersion |
Publisher
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| departments |
Science and Technology
Technical Support Department
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