diplomsko delo
Jan Weissenbach (Author), Aleksander Sadikov (Mentor)

Abstract

Diplomska naloga rešuje problem avtomatskega zaustavljanja naprave za stepanje smetane. Problem rešuje z uporabo algoritmov strojnega učenja na podlagi podatkov obremenjenosti motorja. Smetane imajo med seboj zelo različne karakteristike, zato jih je težko prepoznati in napovedati zaustavitev procesa. Opisane so že obstoječe rešitve za omenjen problem, med drugimi uporaba nevronskih mrež in uporaba klasičnega algoritma. Opisani so podatki in ugotovitve, na podlagi katerih smo se odločili za gradnjo petih napovednih modelov glede na maso. Opisane so značilke in razlog zakaj smo jih uporabili pri učenju samih modelov. Prav tako so predstavljeni rezultati omenjenih modelov.

Keywords

klasifikacija;MATLAB;časovna serija;računalništvo in informatika;visokošolski strokovni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [J. Weissenbach]
UDC: 004.85(043.2)
COBISS: 76574211 Link will open in a new window
Views: 225
Downloads: 2
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Other data

Secondary language: English
Secondary title: Automated stopping of the cream-whipping machine using machine learning
Secondary abstract: This thesis solves the problem for automatic stop of a device for whipping cream. The problem is solved using classic machine learning algorithms based on motor load. Creams have different characteristics and are hard to recognise and it is even harder to predict the stopping point. It describes already existing solutions such as usage of neural networks and classic algorithm. We have described used data and findings based on which we have created five different classification models. We have described used statistic metrics and presented model results.
Secondary keywords: machine learning;classification;MATLAB;time-series;computer science;computer and information science;diploma thesis;Strojno učenje;Umetna inteligenca;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000470
Embargo end date (OpenAIRE): 2022-09-06
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 35 str.
ID: 13328276