Otkrivanje fizikalnih izraza genetskim programiranjem

master's thesis

• Title (english): Discovering physical expressions using genetic programming
• Author: Filip Prevendar
• Mentor: Marko Đurasević (mentor)
• Committee member: Marko Đurasević (predsjednik povjerenstva)
• Committee member: Domagoj Jakobović (član povjerenstva)
• Committee member: Željka Mihajlović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2022-07-04, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom radu pokušava se otkriti 100 jednadžbi iz fizike u obliku y = f(x) koje su zadane kao skup točaka x i pripadne vrijednosti y.
Takav problem naziva se simbolička regresija i u ovom radu se rješava pomoću genetskog programiranja, posebnog oblika genetskog algoritma gdje su jedinke stabla umjesto vektora vrijednosti fiksne veličine.

Abstract (english)

In this thesis 100 equations from physics are attempted to be guessed. The equations are in a form y = f(x) where x is given as a set of points, and y is associated value with the given point. Such problem is called symbolic regression and in this thesis, the problem is tackled with genetic programming, a special case of genetic algorithm where instead of using vectors with fixed length containing values, trees are used as a solution.

• Keywords: simbolička regresija; genetsko programiranje
• Keywords (english): symbolic regression; genetic programming}
• Language: croatian
• URN:NBN: urn:nbn:hr:168:389411
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 09:44:31