Naslov
A Method of Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning

Autori
Golub Medvešek, Ivana

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, doktorska disertacija

Fakultet
Pomorski fakultet

Mjesto
Split

Datum
16.07

Godina
2021

Stranica
96

Mentor
Dodig, Hrvoje ; Leder, Nenad

Ključne riječi
International Hydrographic Organisation, survey categories, IHO regions, stranding, supervised learning, decision tree, hydrographic survey, weighted sum model, multidecision, criteria, survey technologies

Sažetak
Hydrographic survey or seabed mapping plays an important role in achieving better maritime safety, especially in coastal waters. Due to advances in survey technologies, it becomes important to choose well-suited technology for a specific area. Moreover, various technologies have various ranges of equipment and manufacturers, as well as characteristics. Therefore, in this thesis, a proposed method of a hydrographic survey, i.e., identifying the appropriate technology, has been developed. The method is based on a reduced elimination matrix, decision tree supervised learning, and multicriteria decision methods. The available technologies were: SBES (research vessel), SBES+SSS (research vessel), MBES (research vessel), MBES (research vessel)+SBES (small boat), LIDAR (UAV), SDB (satellite sensors) and they are applied as a case study of Kaštela Bay. The optimal technology for Kaštela Bay study case was MBES (research vessel) and MBES (research vessel) + SBES (small boat) with a score of 0.97. Then with a score of 0.82 follows the SDB technology. Other available alternatives have a significantly lower score. It is a small evident difference between the three alternatives SBES (research vessel), SBES+SSS (research vessel), and LIDAR, which have a WSM score in the range from 0.58 – 0.65.

Izvorni jezik
Engleski

Znanstvena područja
Tehnologija prometa i transport, Interdisciplinarne tehničke znanosti

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