Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis

Baković, Josipa

prikaz prve stranice dokumenta Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis

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undergraduate thesis

Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis

Rijeka: University of Rijeka, Faculty of Maritime Studies, Rijeka, 2023. urn:nbn:hr:187:525356

Baković, Josipa

University of Rijeka
Faculty of Maritime Studies, Rijeka
Department of Marine Electronics and Communications

Cite this document

APA 6th Edition

Baković, J. (2023). Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Maritime Studies, Rijeka. Retrieved from https://urn.nsk.hr/urn:nbn:hr:187:525356

MLA 8th Edition

Baković, Josipa. "Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis." Undergraduate thesis, University of Rijeka, Faculty of Maritime Studies, Rijeka, 2023. https://urn.nsk.hr/urn:nbn:hr:187:525356

Chicago 17th Edition

Harvard

Baković, J. (2023). 'Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis', Undergraduate thesis, University of Rijeka, Faculty of Maritime Studies, Rijeka, accessed 13 July 2024, https://urn.nsk.hr/urn:nbn:hr:187:525356

Vancouver

Baković J. Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Maritime Studies, Rijeka; 2023 [cited 2024 July 13] Available at: https://urn.nsk.hr/urn:nbn:hr:187:525356

IEEE

J. Baković, "Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis", Undergraduate thesis, University of Rijeka, Faculty of Maritime Studies, Rijeka, Rijeka, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:187:525356

Cite this item: https://urn.nsk.hr/urn:nbn:hr:187:525356

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Metadata

Title	Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis
Title (croatian)	Poboljšanje iskorištavanja pomorskih podataka putem naprednih tehnika strojnog učenja u analizi AIS podataka
Author	Josipa Baković
Mentor	Irena Jurdana (mentor)
Mentor	Nikola Lopac (komentor)
Granter	University of Rijeka Faculty of Maritime Studies, Rijeka (Department of Marine Electronics and Communications) Rijeka
Defense date and country	2023-07-10, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Traffic and Transport Technology
Abstract	This bachelor's thesis reviews the literature on the application of diverse machine learning (ML) methods in the maritime industry, specifically focusing on automatic identification system (AIS) data. The review explores a wide range of ML techniques, such as neural networks, reinforcement learning, classification, regression, and clustering, and their utilization to enhance maritime operations, efficiency, and safety. Demonstrating positive results, various studies highlight the effectiveness of these methods as well as several shortcomings that are sought to be corrected in further research. Furthermore, the thesis identifies potential future applications of ML in fleet management, vessel maintenance, and navigational safety analysis. In summary, the thesis presents practical insights through the application of selected ML methods to real AIS data, yielding meaningful results for the maritime industry.
Abstract (croatian)	Ovaj završni rad pruža pregled literature o primjeni različitih metoda strojnog učenja u pomorstvu, fokusirajući se na podatke automatskog identifikacijskog sustava (AIS). Prikazane su različite primjene metoda strojnog učenja u područjima poput pomorske sigurnosti, praćenja brodova, optimizacije rute, detekcije anomalija i predikcije ponašanja brodova. Demonstrirajući pozitivne rezultate, različita istraživanja ističu učinkovitost tih metoda kao i nekolicinu nedostataka koji se nastoje ispraviti u daljnjim istraživanjima. Nadalje, rad identificira potencijalne buduće primjene metoda strojnog učenja u upravljanju flotom, održavanju brodova i analizi navigacijske sigurnosti. Ukratko, rad pruža praktične uvide kroz primjenu odabranih metoda na stvarnim AIS podacima, donoseći značajne rezultate za pomorsku industriju.
Keywords
Keywords (croatian)
Language	english
URN:NBN	urn:nbn:hr:187:525356
Study programme	Title: Marine Electronic Engineering and Information Technology Study programme type: university Study level: undergraduate Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektroničke i informatičke tehnologije (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektroničke i informatičke tehnologije)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Repository	Repository of the University of Rijeka, Faculty of Maritime Studies - FMSRI Repository
Created on	2023-07-05 18:48:32