Navigators’ Behavior Analysis Using Data Mining
One of the ways to prevent accidents at sea is to detect risks caused by humans and to counteract them. These tasks can be executed through an analysis of ship maneuvers and the identification of behavior considered to be potentially dangerous, e.g., based on data obtained online from the automatic...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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MDPI AG
2020-01-01
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Series: | Journal of Marine Science and Engineering |
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Online Access: | https://www.mdpi.com/2077-1312/8/1/50 |
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author | Zbigniew Pietrzykowski Miroslaw Wielgosz Marcin Breitsprecher |
author_facet | Zbigniew Pietrzykowski Miroslaw Wielgosz Marcin Breitsprecher |
author_sort | Zbigniew Pietrzykowski |
collection | DOAJ |
description | One of the ways to prevent accidents at sea is to detect risks caused by humans and to counteract them. These tasks can be executed through an analysis of ship maneuvers and the identification of behavior considered to be potentially dangerous, e.g., based on data obtained online from the automatic identification system (AIS). As a result, additional measures or actions can be taken, e.g., passing at a distance greater than previously planned. The detection of risks at sea requires a prior definition of behavior patterns and the criteria assigned to them. Each pattern represents a specific navigator’s safety profile. The criteria assigned to each pattern for the identification of the navigator’s safety profile were determined from previously recorded AIS data. Due to a large amount of data and their complex relationships, these authors have proposed to use data mining tools. This work continues previous research on this subject. The conducted analysis covered data recorded in simulation tests done by navigators. Typical ship encounter situations were included. Based on additional simulation data, the patterns of behavior were verified for the determination of a navigator’s safety profile. An example of using the presented method is given. |
first_indexed | 2024-12-20T13:50:35Z |
format | Article |
id | doaj.art-b4d499550da34909857ad91e73b21da8 |
institution | Directory Open Access Journal |
issn | 2077-1312 |
language | English |
last_indexed | 2024-12-20T13:50:35Z |
publishDate | 2020-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Journal of Marine Science and Engineering |
spelling | doaj.art-b4d499550da34909857ad91e73b21da82022-12-21T19:38:33ZengMDPI AGJournal of Marine Science and Engineering2077-13122020-01-01815010.3390/jmse8010050jmse8010050Navigators’ Behavior Analysis Using Data MiningZbigniew Pietrzykowski0Miroslaw Wielgosz1Marcin Breitsprecher2Faculty of Computer Science and Telecommunication, Maritime University of Szczecin, 70-500 Szczecin, PolandFaculty of Navigation, Maritime University of Szczecin, 70-500 Szczecin, PolandFaculty of Computer Science and Telecommunication, Maritime University of Szczecin, 70-500 Szczecin, PolandOne of the ways to prevent accidents at sea is to detect risks caused by humans and to counteract them. These tasks can be executed through an analysis of ship maneuvers and the identification of behavior considered to be potentially dangerous, e.g., based on data obtained online from the automatic identification system (AIS). As a result, additional measures or actions can be taken, e.g., passing at a distance greater than previously planned. The detection of risks at sea requires a prior definition of behavior patterns and the criteria assigned to them. Each pattern represents a specific navigator’s safety profile. The criteria assigned to each pattern for the identification of the navigator’s safety profile were determined from previously recorded AIS data. Due to a large amount of data and their complex relationships, these authors have proposed to use data mining tools. This work continues previous research on this subject. The conducted analysis covered data recorded in simulation tests done by navigators. Typical ship encounter situations were included. Based on additional simulation data, the patterns of behavior were verified for the determination of a navigator’s safety profile. An example of using the presented method is given.https://www.mdpi.com/2077-1312/8/1/50behavior patternssea navigationsafety profiledata mining |
spellingShingle | Zbigniew Pietrzykowski Miroslaw Wielgosz Marcin Breitsprecher Navigators’ Behavior Analysis Using Data Mining Journal of Marine Science and Engineering behavior patterns sea navigation safety profile data mining |
title | Navigators’ Behavior Analysis Using Data Mining |
title_full | Navigators’ Behavior Analysis Using Data Mining |
title_fullStr | Navigators’ Behavior Analysis Using Data Mining |
title_full_unstemmed | Navigators’ Behavior Analysis Using Data Mining |
title_short | Navigators’ Behavior Analysis Using Data Mining |
title_sort | navigators behavior analysis using data mining |
topic | behavior patterns sea navigation safety profile data mining |
url | https://www.mdpi.com/2077-1312/8/1/50 |
work_keys_str_mv | AT zbigniewpietrzykowski navigatorsbehavioranalysisusingdatamining AT miroslawwielgosz navigatorsbehavioranalysisusingdatamining AT marcinbreitsprecher navigatorsbehavioranalysisusingdatamining |