An Improvement on Estimated Drifter Tracking through Machine Learning and Evolutionary Search

In this study, we estimated drifter tracking over seawater using machine learning and evolutionary search techniques. The parameters used for the prediction are the hourly position of the drifter, the wind velocity, and the flow velocity of each drifter position. Our prediction model was constructed...

書誌詳細
出版年:	Applied Sciences
主要な著者:	Yong-Wook Nam, Hwi-Yeon Cho, Do-Youn Kim, Seung-Hyun Moon, Yong-Hyuk Kim
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2020-11-01
主題:	drifter trajectory evolutionary computation machine learning deep learning NCLS
オンライン･アクセス:	https://www.mdpi.com/2076-3417/10/22/8123

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