diplomsko delo
Klemen Bec (Author), Vili Podgorelec (Mentor), Sašo Karakatič (Co-mentor)

Abstract

Zaradi sodobne tehnologije, kot so npr. računalniki in internet imamo, v današnjem času, na voljo zelo veliko podatkov. To je tudi eden izmed glavnih razlogov, zakaj je postalo strojno učenje tako popularno. Med podatki so tudi podatki o vremenu, ki jih pridobivamo s satelitov, zračnih balonov in vremenskih postaj na Zemlji. Zato sem se odločil, da bom izdelal aplikacijo, ki bo s pomočjo teh podatkov in strojnega učenja napovedala vreme. V diplomskem delu je približno četrtina vsebine namenjena teoriji. Na kratko je predstavljeno napovedovanje vremena in strojno učenje. Opisano je, kako sta ta dva področja med sabo povezana v praksi. V zadnjem delu teorije so opisane uporabljene metode strojnega učenja in merila kakovosti. Predstavljeni so tudi uporabljeni programi in tehnologije. Predvsem pa je diplomsko delo osredotočeno na izdelavo aplikacije za napovedovanje vremena. Na koncu je predstavljena uporaba aplikacije. Podani so končni rezultati in zapisane so ugotovitve.

Keywords

strojno učenje;nevronske mreže;priprava podatkov;vremenska napoved;linearna regresija;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: K. Bec
UDC: 004.777:004.8(043.2)
COBISS: 21788950 Link will open in a new window
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Downloads: 157
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Other data

Secondary language: English
Secondary title: Design and development of an application for weather prediction using machine learning
Secondary abstract: Because of modern technology, such as computers and the Internet we have a lot of data available today. This is also one of the main reasons why machine learning has become so popular. There is also a lot of weather data obtained from satellites, airborne balloons and weather stations on the ground. That's why I decided to create an application that will predict weather using this data and machine learning. In the diploma thesis, approximately a quarter of the content is devoted to theory. In brief, weather forecasting and machine learning are presented. It is described how these two areas are interconnected in practice. The last part of the theory describes used machine learning methods and quality metrics. There is also presentation of used programs and technologies. Above all, the thesis focuses on creating an application for weather forecasting. Finally, the use of the application is presented. The final results are given and the findings are recorded.
Secondary keywords: machine learning;neural network;data preparation;weather report;linear regression;keras;
URN: URN:SI:UM:
Type (COBISS): Bachelor thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Informatika in tehnologije komuniciranja
Pages: IX, 62 str.
ID: 10959075