機械学習に基づく流体変数の未来予測と数学的背景
齊木吉隆(一橋大学)

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.

• http://saiki.hub.hit-u.ac.jp/

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