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 |
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論文番号 | 1157 |
ジャーナル | Plasma and Fusion Research |
巻 | 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