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undergraduate thesis
Jednostavni nelinearni model za predviđanje COVID-19
2020. urn:nbn:hr:166:878324
Škalec, Lucia
University of Split
Faculty of Science
Department of Physics

Cite this document

Škalec, L. (2020). Jednostavni nelinearni model za predviđanje COVID-19 (Undergraduate thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:878324

Škalec, Lucia. "Jednostavni nelinearni model za predviđanje COVID-19." Undergraduate thesis, University of Split, Faculty of Science, 2020. https://urn.nsk.hr/urn:nbn:hr:166:878324

Škalec, Lucia. "Jednostavni nelinearni model za predviđanje COVID-19." Undergraduate thesis, University of Split, Faculty of Science, 2020. https://urn.nsk.hr/urn:nbn:hr:166:878324

Škalec, L. (2020). 'Jednostavni nelinearni model za predviđanje COVID-19', Undergraduate thesis, University of Split, Faculty of Science, accessed 25 April 2024, https://urn.nsk.hr/urn:nbn:hr:166:878324

Škalec L. Jednostavni nelinearni model za predviđanje COVID-19 [Undergraduate thesis]. Split: University of Split, Faculty of Science; 2020 [cited 2024 April 25] Available at: https://urn.nsk.hr/urn:nbn:hr:166:878324

L. Škalec, "Jednostavni nelinearni model za predviđanje COVID-19", Undergraduate thesis, University of Split, Faculty of Science, Split, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:166:878324

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Metadata
TitleJednostavni nelinearni model za predviđanje COVID-19
Title (english)A simple non-linear model for predicting COVID-19
AuthorLucia Škalec
MentorŽarko Kovač (mentor)
Committee memberŽarko Kovač (predsjednik povjerenstva)
Committee memberIvana Weber (član povjerenstva)
Committee memberJadranka Šepić (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Physics)
Split
Defense date and country2020-09-21, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Abstract
SARS-CoV-2 novootkriveni virus, uzročnik bolesti COVID-19, započeo je sa svojim širenjem iz Kine krajem 2019. godine. Od tada države uz pomoć znanstvene zajednice pokušavaju pronaći načine kako bi predvidjele i suzbile daljnje širenje virusa. Jedan od načina predviđanja porasta broja oboljelih je i pomoću jednostavnih matematičkih modela koji nam daju uvid u to kako će se kretati brojevi oboljelih, te kada bi se mogao doseći maksimalan broj oboljelih u pojedinoj državi. U ovome radu promotrit ćemo i analizirati podatke o broju zaraženih od COVID-19 u nekoliko europskih zemalja u razdoblju od 25. siječnja 2020. do 17. lipnja 2020. godine. Na temelju analize podataka koja je provedena u Matlab-u dolazimo do zaključka da se kretanje broja zaraženih može opisati pomoću nelinearne matematičke jednadžbe. Relacija kojom smo opisali krivulju kretanja broja zaraženih odgovarala je za svaku promatranu zemlju, te smo zaključili da se u različitim zemljama podaci o broju oboljelih osoba ponašaju na sličan način. Usporedbom modela sa stvarnim podacima o broju zaraženih, model je predvidio najpreciznije rezultate kada je broj oboljelih bio već dosta visok, te kada je vremensko razdoblje predviđanja bilo kraće.
Abstract (english)
SARS-CoV-2 is a newly discovered virus, causative agent of a disease called COVID-19, which has begun its spreading from China at the end of 2019. Since then countries with a help on a scientific community are trying their best to find the ways to predict and suppress further spreading of the virus. One of the ways of predicting the number of infected people is by building simple mathematical models which will give us an insight into the movement of number of infected, as well as when should we expect a maximum number of infected people within every country. In this thesis we will examine and analyse the data set which contains the number of infected people by COVID-19 in several European countries from 25th of January 2020 until 17th of June 2020. From this data analysis which was carried out in Matlab we concluded that the movement of the number of infected people can be described by non-linear mathematical equation. Using this relation we have built the simple model for predicting COVID-19. Results showed that the prediction of the model was very accurate when the number of infected people was very high and when the time period was smaller.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:878324
Study programmeTitle: Physics
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) fizike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) fizike)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
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Created on2021-01-15 14:24:19