Prediktivno modeliranje godišnjih stopa nataliteta i mortaliteta u Republici Hrvatskoj na temelju demografskih i ekonomskih varijabli

undergraduate thesis

• Title (english): Predictive modeling of the annual natality and mortality rates in the Republic of Croatia based on demographic and economic variables
• Author: Valentina Ivanić
• Mentor: Siniša Popović (mentor)
• Committee member: Siniša Popović (predsjednik povjerenstva)
• Committee member: Hrvoje Nuić (član povjerenstva)
• Committee member: Mate Gambiraža (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2024-07-03, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Rad se temelji na prediktivnom modeliranju nataliteta i mortaliteta u Republici Hrvatskoj. Cilj je identificirati ključne varijable koje utječu na promjene broja rođenih i umrlih te izgradnja predikcijskih modela. Koriste se sljedeći modeli: linearna regresija, Holt, Holt-Winters, ARIMAX, XGBoost. Rezultati pokazuju da su jednostavni modeli poput linearne regresije i Holtove metode dovoljno dobri za ovakav problem. Većina modela ima zadovoljavajuće performanse te prati trendove u podatcima. Bolje performanse su ostvarene kod predikcija za mortalitet.

Abstract (english)

The study is based on predictive modeling of birth and mortality rate in Republic of Croatia. The aim is to identify key variables that influence changes in number of births and deaths and to develop predictive models. Following models were used: linear regression, Holt, ARIMAX, XGBoost. The results show that simple models like linear regression and Holt are sufficient for this problem. Most models have good performance and follow data trends. Better performances were achieved for mortality predictions.

• Keywords: mortalitet; natalitet; stanovništvo; linearna regresija; Holt; ARIMAX; XGBoost; prediktivno modeliranje
• Keywords (english): mortality; birth rate; population; linear regression; Holt; ARIMAX; XGBoost; predictive modeling
• Language: croatian
• URN:NBN: urn:nbn:hr:168:816664
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2024-10-12 20:51:34