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Vessel Classifying and Trajectory Based on Automatic Identification System Data
by
Aisjah, Aulia Siti
, Damastuti, Natalia
, Masroeri, Agoes
in
AIS
/ Automatic identification
/ Automatic Identification System
/ Classification
/ Data mining
/ Data processing
/ Identification systems
/ Root-mean-square errors
/ Ships
/ Vessel
/ Vessels
/ XG-Boost
2021
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Vessel Classifying and Trajectory Based on Automatic Identification System Data
by
Aisjah, Aulia Siti
, Damastuti, Natalia
, Masroeri, Agoes
in
AIS
/ Automatic identification
/ Automatic Identification System
/ Classification
/ Data mining
/ Data processing
/ Identification systems
/ Root-mean-square errors
/ Ships
/ Vessel
/ Vessels
/ XG-Boost
2021
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Do you wish to request the book?
Vessel Classifying and Trajectory Based on Automatic Identification System Data
by
Aisjah, Aulia Siti
, Damastuti, Natalia
, Masroeri, Agoes
in
AIS
/ Automatic identification
/ Automatic Identification System
/ Classification
/ Data mining
/ Data processing
/ Identification systems
/ Root-mean-square errors
/ Ships
/ Vessel
/ Vessels
/ XG-Boost
2021
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Vessel Classifying and Trajectory Based on Automatic Identification System Data
Journal Article
Vessel Classifying and Trajectory Based on Automatic Identification System Data
2021
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Overview
Nowadays, the development of the of Automatic Identification System (AIS) device has continuously increased. It was initially used to send information on the whereabouts of ships to avoid collisions, but with stored data, it is used for monitoring waters. Therefore, this study was carried out using AIS data to classify ships in Indonesian waters. Based on features such as length, width, and weight, it classified them into 9 types of vessels. The data mining process was used to characterize each type with the ensemble method. Furthermore, data processing was carried out to determine the ship’s trajectory pattern. In this study, 80% of training data was used while the rest were testing data. The results showed that an accuracy value of 99.8% was obtained with a Root Mean Square Error (RMSE) value of 0.12.
Publisher
IOP Publishing
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