Classifying vessels operating in the South China Sea by origin with the Automatic Identification System
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Authors
Cull, Kimberly M.
Subjects
data analysis
classification
Automatic Identification System
South China Sea
gradient boosted models
classification
Automatic Identification System
South China Sea
gradient boosted models
Advisors
Whitaker, Lyn R.
Date of Issue
2018-03
Date
Mar-18
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
This research focuses on building classification models with multinomial responses based upon seven months of Automatic Identification System (AIS) data gathered from the South China Sea. The models, built using Gradient Boosted Machines (GBM), assess the validity of utilizing AIS to confirm an operating vessel’s origin, by country and geographical region. Two types of models are built. The first model captures the naturally dependent nature of AIS signals and serves as a proof of concept for how well a global model trained over many years could perform The second model attempts to reduce the dependency between AIS signals in order to characterize maritime patterns of behavior by country and region. With relative accuracy, both types of models are able to predict a vessel’s origin and provide insight into maritime patterns of behavior.
Type
Thesis
Description
Series/Report No
Department
Operations Analysis
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.