Improving maritime awareness with semantic genetic programming and linear scaling: Prediction of vessels position based on AIS data

Leonardo Vanneschi, Mauro Castelli, Ernesto Costa, Alessandro Re, Henrique Vaz, Vítor Lobo, Paulo Urbano

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Maritime domain awareness deals with the situational understanding of maritime activities that could impact the security, safety, economy or environment. It enables quick threat identification, informed decision making, effective action support, knowledge sharing and more accurate situational awareness. In this paper, we propose a novel computational intelligence framework, based on genetic programming, to predict the position of vessels, based on information related to the vessels past positions in a specific time interval. Given the complexity of the task, two well known improvements of genetic programming, namely geometric semantic operators and linear scaling, are integrated in a new and sophisticated genetic programming system. The work has many objectives, for instance assisting more quickly and effectively a vessel when an emergency arises or being able to chase more efficiently a vessel that is accomplishing illegal actions. The proposed system has been compared to two different versions of genetic programming and three non-evolutionary machine learning methods, outperforming all of them on all the studied test cases.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - 18th European Conference, EvoApplications 2015, Proceedings
PublisherSpringer-Verlag
Pages732-744
Number of pages13
Volume9028
ISBN (Electronic)9783319165486
DOIs
Publication statusPublished - 2015
Event18th European Conference on the Applications of Evolutionary Computation, EvoApplications 2015 - Copenhagen, Denmark
Duration: 8 Apr 201510 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9028
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference18th European Conference on the Applications of Evolutionary Computation, EvoApplications 2015
CountryDenmark
CityCopenhagen
Period8/04/1510/04/15

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