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Prediction of drowning person‘s route using machine learning for meteorological information of maritime observation buoy

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(3), pp.1-12
  • DOI : 10.9708/jksci.2022.27.03.001
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : November 4, 2021
  • Accepted : March 14, 2022
  • Published : March 31, 2022

Jung-Wook Han 1 Hoseok Moon 2

1대한민국해군 제6항공전단
2국방대학교

Accredited

ABSTRACT

In the event of a maritime distress accident, rapid search and rescue operations using rescue assets are very important to ensure the safety and life of drowning person’s at sea. In this paper, we analyzed the surface layer current in the northwest sea area of Ulleungdo by applying machine learning such as multiple linear regression, decision tree, support vector machine, vector autoregression, and LSTM to the meteorological information collected from the maritime observation buoy. And we predicted the drowning person’s route at sea based on the predicted current direction and speed information by constructing each prediction model. Comparing the various machine learning models applied in this paper through the performance evaluation measures of MAE and RMSE, the LSTM model is the best. In addition, LSTM model showed superior performance compared to the other models in the view of the difference distance between the actual and predicted movement point of drowning person.

Citation status

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