Prediction of the marine spreading of low sulfur fuel oil using the long short-term memory model trained with three-phase numerical simulations-Reference-Cited by-同舟云学术

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Prediction of the marine spreading of low sulfur fuel oil using the long short-term memory model trained with three-phase numerical simulations

Published:2024-05 Issue: Volume:202 Page:116356
ISSN:0025-326X
Container-title:Marine Pollution Bulletin
language:en
Short-container-title:Marine Pollution Bulletin

Author:

Lee Jaebeen,Park Hyungmin

Funder

Korea Coast Guard

Institute of Engineering Research, Seoul National University

Korea Institute of Marine Science and Technology Promotion

Publisher

Elsevier BV

Reference69 articles.

1. Evaluation of data preprocessing and feature selection process for prediction of hourly PM10 concentration using long short-term memory models;Aksangür;Environ. Pollut.,2022

2. Sensors, features, and machine learning for oil spill detection and monitoring: a review;Al-Ruzouq;Remote Sens.,2020

3. A cross-scale numerical modeling system for management support of oil spill accidents;Azevedo;Mar. Pollut. Bull.,2014

4. ModAugNet: a new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module;Baek;Expert Syst. Appl.,2018

5. The oil spill model OILTRANS and its application to the Celtic Sea;Berry;Mar. Pollut. Bull.,2012

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