言語種別 英語 発行・発表の年月 2022/03 形態種別 学術雑誌 査読 査読あり 標題 Machine learning‑based turbulence‑risk　prediction method for the safe operation　of aircrafts 執筆形態 共著 掲載誌名 Journal of Big Data 掲載区分 国外 巻・号・頁 9(29（2022）),pp.1-16 著者・共著者 ◎Shinnya Mizuno,　Haruka Ohba,　Koji Ito   ◎水野信也　大場春佳　伊藤貢司 概要 This study has proposed a method for detecting turbulence, a primary factor that influences safe aircraft operation. Thus, this study proposed a method for predicting turbulence occurrence based on the turbulence occurrence date information provided by airlines as well as meteorological data sets obtained from open data available in Japan as teacher data. However, because commonly used machine learning methods are unable to detect the turbulence occurrence date, the proposed method employed principal component analysis coupled with the K-Means method to generate risk clusters with a high likelihood of turbulence occurrence and consequently perform statistical checks. Subsequently, the risk clusters were utilized as supervisory data for turbulence occurrence, while the support vector machine was used for predicting turbulence occurrence. researchmap用URL https://doi.org/10.1186/s40537-022-00584-5