Online Prediction of Ship Behavior with Automatic Identification System Sensor Data Using Bidirectional Long Short-Term Memory Recurrent Neural Network

Online Prediction of Ship Behavior with Automatic Identification System Sensor Data Using Bidirectional Long Short-Term Memory Recurrent Neural Network

The real-time prediction of ship behavior plays an important role in navigation and intelligent collision avoidance systems. This study developed an online real-time ship behavior prediction model by constructing a bidirectional long short-term memory recurrent neural network (BI-LSTM-RNN) that is s...

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Bibliographic Details
Main Authors: Miao Gao, Guoyou Shi, Shuang Li
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Sensors
Subjects:
ship behavior
machine learning
online prediction
AIS sensor data
big data
Online Access:https://www.mdpi.com/1424-8220/18/12/4211

Internet

https://www.mdpi.com/1424-8220/18/12/4211

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