採択課題 【詳細】
| jh190070-MDJ | 機械学習に基づく流体変数の未来予測と数学的背景 |
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| 課題代表者 | 齊木吉隆(一橋大学) Yoshitaka Saiki (Hitotsubashi University) |
| 概要 | We construct a data-driven dynamical system model for a macroscopic variable of a high-dimensionally chaotic fluid flow by training its time-series data. We use a machine-learning approach, the reservoir computing for the construction of the model, and do not use the knowledge of a physical process of fluid dynamics in its procedure. |
| 報告書等 | 研究紹介ポスター ／ 最終報告書 |
| 関連Webページ |
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