[M-GI34] 情報地球惑星科学と大量データ処理情報

[MGI34-P07] 機械学習・数値シミュレーション・観測による宇宙プラズマ現象研究に向けた学習データの整備

*深沢 圭一郎¹、木村 智樹²、徳永 旭将³、中野 慎也⁴ (1.京都大学学術情報メディアセンター、2.東北大学学際科学フロンティア研究所、3.九州工業大学大学院情報工学研究院、4.統計数理研究所モデリング研究系)

キーワード：機械学習、宇宙プラズマ、データベース

The machine learning (ML) has become a powerful tool to find the relation between variables thanks to the deep learning technique. This performs greatly in the classification, regression and recently generative modeling in the engineering and commercial areas. However, due to the satisfaction of physical laws in the scientific research area, the application of ML has some difficulties. In particular, the generative modeling is very sensitive to scientific data since the generated data is not guaranteed by the physical laws.

To overcome these problems, we have tried to apply ML to space plasma physics for several years and then reconfirmed the importance of preparing the training data. For example, when we classify the aurora in the observation results with ML, we have to prepare the huge amount of aurora observational image to learn the feature with high accuracy. It takes a lot of time to prepare the aurora image if considering the augmentation. Thus, we are developing the web site to classify the image including the aurora or not with the expectation of citizen science cooperation. In this study we show the web site for preparing the classification image and the initial results of it. In addition, our database of global simulation data of magnetosphere using real solar wind data and formatted aurora image by All-Sky-Imager will be shown.