ID | 118128 |
著者 |
Horihata, Daichi
Tokushima University
桑原, 明伸
Tokushima University
瀧川, 喜義
Shikoku Research Institute
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資料タイプ |
学術雑誌論文
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抄録 | This paper describes a statistical correction model for wind speed data of the Meso-Scale Model Grid Point Value (MSM-GPV), which is one of the numerical weather forecasting systems. In the numerical forecasting system, there are calculation errors caused by both the physical modeling and estimation of initial values. Because numerical forecast data have two-dimensional spatial information, convolution with a convolutional neural network (CNN) is used to grasp and correct the two-dimensional features of errors contained in the forecast data. In the simulations, several MSM-GPV data used for the input data and various correction models are prepared and compared with the results of a fully connected neural network from the viewpoints of the error improvement rate and error distribution.
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掲載誌名 |
Journal of Signal Processing
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ISSN | 18801013
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出版者 | Research Institute of Signal Processing
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巻 | 24
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号 | 4
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開始ページ | 195
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終了ページ | 198
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発行日 | 2020-07-15
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備考 | 利用は著作権の範囲内に限られる。
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EDB ID | |
出版社版DOI | |
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言語 |
eng
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著者版フラグ |
出版社版
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部局 |
理工学系
技術支援部
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