Spatio-Temporal Network for Sea Fog Forecasting

Sea fog can seriously affect schedules and safety by reducing visibility during marine transportation. Therefore, the forecasting of sea fog is an important issue in preventing accidents. Recently, in order to forecast sea fog, several deep learning methods have been applied to time series data cons...

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Veröffentlicht in:	Sustainability Jg. 14; H. 23; S. 16163
Hauptverfasser:	Park, Jinhyeok, Lee, Young Jae, Jo, Yongwon, Kim, Jaehoon, Han, Jin Hyun, Kim, Kuk Jin, Kim, Young Taeg, Kim, Seoung Bum
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.12.2022
Schlagworte:	Airports Analysis Artificial intelligence Climate change Deep learning deep learning; encoder-decoder structure; forecasting; multi-modal learning; sea fog Fog Forecasting Forecasts and trends Humidity Machine learning Neural networks Numerical analysis Ports Precipitation forecasting Shipping industry Support vector machines Technology application Time series South Korea
ISSN:	2071-1050, 2071-1050
Online-Zugang:	Volltext
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