prikaz prve stranice dokumenta Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm
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Scientific paper - Original scientific paper
Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm
Pomorstvo, 34 (2020), 2; 323-337. https://doi.org/10.31217/p.34.2.13
Anđelić, Nikola; Baressi Šegota, Sandi; Lorencin, Ivan; Car, Zlatan

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Anđelić, N., Baressi Šegota, S., Lorencin, I. & Car, Z. (2020). Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm. Pomorstvo, 34. (2), 323-337. doi: 10.31217/p.34.2.13

Anđelić, Nikola, et al. "Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm." Pomorstvo, vol. 34, no. 2, 2020, pp. 323-337. https://doi.org/10.31217/p.34.2.13

Anđelić, Nikola, Sandi Baressi Šegota, Ivan Lorencin and Zlatan Car. "Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm." Pomorstvo 34, no. 2 (2020): 323-337. https://doi.org/10.31217/p.34.2.13

Anđelić, N., et al. (2020) 'Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm', Pomorstvo, 34(2), pp. 323-337. doi: 10.31217/p.34.2.13

Anđelić N, Baressi Šegota S, Lorencin I, Car Z. Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm. Pomorstvo [Internet]. 2020 December [cited 2024 June 17];34(2):323-337. doi: 10.31217/p.34.2.13

N. Anđelić, S. Baressi Šegota, I. Lorencin and Z. Car, "Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm", Pomorstvo, vol. 34, no. 2, pp. 323-337, December 2020. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:187:662212. [Accessed: 17 June 2024]

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Metadata
Title (english)Estimation of gas turbine shaft torque and fuel flow of a CODLAG propulsion system using genetic programming algorithm
AuthorNikola Anđelić
AuthorSandi Baressi Šegota https://orcid.org/0000-0002-3015-1024
AuthorIvan Lorencin
AuthorZlatan Car https://orcid.org/0000-0003-2817-9252
Author's institutionUniversity of Rijeka
Faculty of Engineering
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Abstract (english)
In this paper, the publicly available dataset of condition based maintenance of combined diesel-electric and gas (CODLAG) propulsion system for ships has been utilized to obtain symbolic expressions which could estimate gas turbine shaft torque and fuel flow using genetic programming (GP) algorithm. The entire dataset consists of 11934 samples that was divided into training and testing portions of dataset in an 80:20 ratio. The training dataset used to train the GP algorithm to obtain symbolic expressions for gas turbine shaft torque and fuel flow estimation consisted of 9548 samples. The best symbolic expressions obtained for gas turbine shaft torque and fuel flow estimation were obtained based on their R2 score generated as a result of the application of the testing portion of the dataset on the aforementioned symbolic expressions. The testing portion of the dataset consisted of 2386 samples. The three best symbolic expressions obtained for gas turbine shaft torque estimation generated R2 scores of 0.999201, 0.999296, and 0.999374, respectively. The three best symbolic expressions obtained for fuel flow estimation generated R2 scores of 0.995495, 0.996465, and 0.996487, respectively.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titlePomorstvo
Numberingvol. 34, no. 2, pp. 323-337
p-ISSN1332-0718
e-ISSN1846-8438
DOIhttps://doi.org/10.31217/p.34.2.13
URN:NBNurn:nbn:hr:187:662212
Publication2020-12
Document URLhttps://hrcak.srce.hr/247799
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-02-28 15:54:24