Naslov
Machine learning techniques for modeling ships performance in waves

Autori
Grubišić, Luka ; Mandić, Dino ; Mudronja, Luka ; Grubišić, Izvor

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the Transport Research Arena 2018 / - Beč, 2018, 1-10

Skup
7th European Transport Research Arena (TRA 2018)

Mjesto i datum
Beč, Austrija, 16.04.2018. - 19.04.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
polar diagram ; IMU sensor ; machine learning ; performance optimization

Sažetak
This paper presents a design of a system for monitoring and recording the influence of a running sea on a vessel in motion. Our approach is based on machine learning techniques that relate measured wave parameters (encounter angle, wave height and wave amplitude) with measured motion characteristics of the vessel. High quality GRIB data for wave measurements are available for some regions (e.g. North Sea and Adriatic) and we use those for generating training sets. We store this correlation in a neural net and use this information in conjunction with the targeted performance indicator (RMS of linear acceleration, RMS of roll or pitch angle, fuel consumption) to create historical directed performance charts for the vessel in consideration. We use this information for rational route planning and optimization. We report on the conclusions of experiments.

Izvorni jezik
Hrvatski

Znanstvena područja
Računarstvo

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