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master's thesis
Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama
Rijeka: University of Rijeka, Faculty of Engineering, 2020. urn:nbn:hr:190:301999
Žuškin, Sonia
University of Rijeka
Faculty of Engineering
Department of Fluid Mechanics and Computational Engineering
Section of Computational Engineering

Institutional repository: Repository of the University of Rijeka, Faculty of Engineering

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Žuškin, S. (2020). Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:301999

Žuškin, Sonia. "Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama." Master's thesis, University of Rijeka, Faculty of Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:190:301999

Žuškin, Sonia. "Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama." Master's thesis, University of Rijeka, Faculty of Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:190:301999

Žuškin, S. (2020). 'Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 24 December 2024, https://urn.nsk.hr/urn:nbn:hr:190:301999

Žuškin S. Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2020 [cited 2024 December 24] Available at: https://urn.nsk.hr/urn:nbn:hr:190:301999

S. Žuškin, "Analiza podataka o bakteriološkom onečišćenju mora na riječkim plažama", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:190:301999

Metadata
TitleAnaliza podataka o bakteriološkom onečišćenju mora na riječkim plažama
Title (english)Analysis of bacteriological sea pollution data for Rijeka beaches
AuthorSonia Žuškin
MentorSiniša Družeta (mentor)
MentorLado Kranjčević (komentor)
Committee memberGoran Mauša (predsjednik povjerenstva)
Committee memberSandi Ljubić (član povjerenstva)
Committee memberSiniša Družeta (član povjerenstva)
Committee memberLado Kranjčević (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Fluid Mechanics and Computational Engineering)
(Section of Computational Engineering)
Rijeka
Defense date and country2020-05-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Abstract
Napravljena je analiza podataka o bakterijama na riječkim plažama. Uređeni su podaci te je istraženo koje varijable imaju najveći utjecaj na predikcijske modele. Objašnjeni su modeli strojnog učenja: regresor potpornih vektora, Bayesova rubna regresija, Lasso model prilagođen s regresijom najmanjeg kuta, automatska regresija određivanja relevantnosti, pasivno agresivna regresija i Theil-Sen regresor. Izvršena je programska implementacija korištenih modela strojnog učenja. Istražena je uspješnost svakoga modela. Grafički su prikazani predikcije svakog modela. Zaključuje se da najbolju predikciju za dani set daje model regresor potpornih vektora. Najveći utjecaj za predikciju Escherichia coli, prema modelima strojnoga učenja, imaju salinitet i sunčevo zračenje.
Abstract (english)
Data analysis of Rijeka beaches has been made. Data has been processed and the research has been done which variables have most impact on predictions. The machine learning algorithms have been explained. Models that are used: Support vector regression, Bayesian ridge regression, Lasso model fit with least angle regression, Passive aggressive regression and Theil-Sen regression. Program implementation of models have been made, their scores analyzed and graphical display of predictions have been shown. It is concluded that the best prediction for given set is given by support vector regression. The biggest influence for prediction of Escherichia coli, by the machine learning models, have salinity and solar irradiance.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:301999
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2020-08-24 13:14:24