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Pregled bibliografske jedinice broj: 1129444

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


Golub Medvešek, Ivana; Vujović, Igor; Šoda, Joško; Krčum, Maja
A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning // Applied Sciences-Basel, 11 (2021), 11; 4966, 19 doi:10.3390/app11114966 (međunarodna recenzija, članak, znanstveni)


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

Autori
Golub Medvešek, Ivana ; Vujović, Igor ; Šoda, Joško ; Krčum, Maja

Izvornik
Applied Sciences-Basel (2076-3417) 11 (2021), 11; 4966, 19

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Supervised learning ; Decision tree ; Hydrographic survey ; Weighted sum model

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 paper, a novel 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: remotely operated underwater vehicle (ROV), unmanned aerial vehicle (UAV), light detection and ranging (LIDAR), autonomous underwater vehicle (AUV), satellite- derived bathymetry (SDB), and multibeam echosounder (MBES), and they are applied as a case study of Kaštela Bay. Results show, considering the specifics of the survey area, that UAV is the best-suited technology to be used for a hydrographic survey. However, some other technologies, such as SDB come close and can be considered an alternative for hydrographic surveys.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Tehnologija prometa i transport



POVEZANOST RADA


Projekti:
VLASTITA-SREDSTVA-PFST-2019-01 - Istraživanja inovativnih tehnologija u pomorstvu uz opremanje znanstvenog laboratorija Pomorskog fakulteta (RIFOS) (Šoda, Joško, VLASTITA-SREDSTVA - Interni poziv ustanove) ( CroRIS)

Ustanove:
Pomorski fakultet, Split

Profili:

Avatar Url Maja Krčum (autor)

Avatar Url Joško Šoda (autor)

Avatar Url Ivana Golub (autor)

Avatar Url Igor Vujović (autor)

Poveznice na cjeloviti tekst rada:

doi www.mdpi.com

Citiraj ovu publikaciju:

Golub Medvešek, Ivana; Vujović, Igor; Šoda, Joško; Krčum, Maja
A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning // Applied Sciences-Basel, 11 (2021), 11; 4966, 19 doi:10.3390/app11114966 (međunarodna recenzija, članak, znanstveni)
Golub Medvešek, I., Vujović, I., Šoda, J. & Krčum, M. (2021) A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning. Applied Sciences-Basel, 11 (11), 4966, 19 doi:10.3390/app11114966.
@article{article, author = {Golub Medve\v{s}ek, Ivana and Vujovi\'{c}, Igor and \v{S}oda, Jo\v{s}ko and Kr\v{c}um, Maja}, year = {2021}, pages = {19}, DOI = {10.3390/app11114966}, chapter = {4966}, keywords = {Supervised learning, Decision tree, Hydrographic survey, Weighted sum model}, journal = {Applied Sciences-Basel}, doi = {10.3390/app11114966}, volume = {11}, number = {11}, issn = {2076-3417}, title = {A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning}, keyword = {Supervised learning, Decision tree, Hydrographic survey, Weighted sum model}, chapternumber = {4966} }
@article{article, author = {Golub Medve\v{s}ek, Ivana and Vujovi\'{c}, Igor and \v{S}oda, Jo\v{s}ko and Kr\v{c}um, Maja}, year = {2021}, pages = {19}, DOI = {10.3390/app11114966}, chapter = {4966}, keywords = {Supervised learning, Decision tree, Hydrographic survey, Weighted sum model}, journal = {Applied Sciences-Basel}, doi = {10.3390/app11114966}, volume = {11}, number = {11}, issn = {2076-3417}, title = {A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning}, keyword = {Supervised learning, Decision tree, Hydrographic survey, Weighted sum model}, chapternumber = {4966} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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