Ogrodje za samodejno načrtovanje športnih aktivnosti

magistrsko delo

Luka Koprivc (Author), Iztok Fister (Mentor), Grega Vrbančič (Co-mentor)

Abstract

V dobi obilice podatkov se pred nami razprostira bogat nabor informacij in naprednih metod zajemanja. Med temi izstopajo zabeleženi podatki o športnih aktivnostih, ki odpirajo vrata analizi in vizualizaciji, vendar še vedno ohranjajo omejitve pri manipulaciji. V okviru te magistrske naloge je predstavljeno inovativno ogrodje, ki izrabi obstoječe aktivnosti in s pomočjo usmerjenih grafov inteligentno predlaga potek nove športne dejavnosti. V začetku se temeljito posvetimo izzivom področja ter preučimo relevantne raziskave. Sledi podrobna razlaga algoritmov, ki omogočajo učinkovito obvladovanje kompleksnosti problema, hkrati pa predstavimo tudi algoritme za obdelavo samoizmerjenih aktivnosti. Zaključimo s praktično uporabo razvitega ogrodja ter podamo refleksijo o njegovi učinkovitosti in koristnosti.

Keywords

obdelava podatkov;podatkovna znanost;python;športne aktivnosti;magistrske naloge;

Data

Language:	Slovenian
Year of publishing:	2023
Typology:	2.09 - Master's Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[L. Koprivc]
UDC:	004.62.021(043.2)
COBISS:	174214659
Views:	98
Downloads:	13
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Framework for automated sports activity planning
Secondary abstract:	In the era of data, more data and data recording methods exist than ever before. Recorded sports activities data are a newer field of study, and can be used for analysis and visualization. However, the possibilities for their manipulation remain very limited. This thesis presents a solution which uses existing activities and directed graphs to recommend paths of new activities. Firstly, we present this work`s field of research and research similar works. Secondly, we propose a solution which we present thoroughly. We present the algorithms which allow us to manage the solution`s complexity and algorithms for processing the activities. Finally, we present the usage of our solution and share our thoughts on its implementation.
Secondary keywords:	data processing;data science;python;sports activities;
Type (COBISS):	Master's thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Informatika in tehnologije komuniciranja
Pages:	1 spletni vir (1 datoteka PDF (X, 43 f.))
ID:	19843347