prikaz prve stranice dokumenta Enhancing maritime data utilization through advanced machine learning techniques in AIS data analysis
  Download
PDF 962.8 KB
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
Department of Marine Electronics and Communications

Institutional repository: Repository of the University of Rijeka, Faculty of Maritime Studies - FMSRI Repository

Cite this document

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. Retrieved from https://urn.nsk.hr/urn:nbn:hr:187:525356

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

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

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, accessed 30 November 2024, https://urn.nsk.hr/urn:nbn:hr:187:525356

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; 2023 [cited 2024 November 30] Available at: https://urn.nsk.hr/urn:nbn:hr:187:525356

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, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:187:525356

Metadata
TitleEnhancing 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
AuthorJosipa Baković
MentorIrena Jurdana (mentor)
MentorNikola Lopac (komentor)
GranterUniversity of Rijeka
Faculty of Maritime Studies
(Department of Marine Electronics and Communications)
Rijeka
Defense date and country2023-07-10, 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)
Languageenglish
URN:NBNurn:nbn:hr:187:525356
Study programmeTitle: 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 resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-07-05 18:48:32