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All Journal JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science)
Hiroshi Suzuki
Electrical and Electronic Engineering, Tokushima University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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PREDICTION MODEL OF WIND SPEED AND DIRECTION USING DEEP NEURAL NETWORK Anggraini Puspita Sari; Hiroshi Suzuki; Takahiro Kitajima; Takashi Yasuno; Dwi Arman Prasetya
JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Vol 3, No 1 (2020): February 2020
Publisher : Merdeka Malang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jeemecs.v3i1.3946

Abstract

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.
Co-Authors Anggraini Puspita Sari Dwi Arman Prasetya Takahiro Kitajima Takashi Yasuno