Reconstruction of time series observed in linear magnetized plasma PANTA via a machine learning algorithm

Yasuhiro Nariyuki, Makoto Sasaki, Tohru Hada, Shigeru Inagaki

研究成果: ジャーナルへの寄稿学術論文査読

抄録

Reconstruction of turbulence time series in a statistically stationary state is discussed by using a machine learning algorithm. We use data obtained by Langmuir probes in the Plasma Assembly for Nonlinear Turbulence Analysis (PANTA). It is shown that even if the distance between two probes is not adequate to resolve the turbulence, the nonlinear regression via the machine learning can give reconstruction better than those by the linear regression and the linear interpolation. Wave forms and frequency spectra show that drift waves are well reconstructed by the machine learning.

本文言語英語
論文番号1157
ジャーナルPlasma and Fusion Research
14
DOI
出版ステータス出版済み - 2019

ASJC Scopus 主題領域

  • 凝縮系物理学

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