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Title:
Mobilna aplikacija za analizo kolesarskih treningov : diplomsko delo
Authors:
ID
Krajnc, David
(
Author
)
ID
Mlakar, Uroš
(
Mentor
)
More about this mentor...
Files:
UN_Krajnc_David_2021.pdf
(2,14 MB)
MD5: 11E251FB08200C274CC2AC642A7ED946
PID:
20.500.12556/dkum/4a99ba86-0513-4bb4-88ca-b70dcc428781
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Osnovni cilj te diplomske naloge je razvoj aplikacije za analizo kolesarskih aktivnosti ter kolesarjevega počutja skozi dan z algoritmom Apriori in asociacijskimi pravili. Podatke smo pridobivali iz kolesarskega števca ter pametne ure in jih shranjevali v podatkovno bazo iz katere smo kasneje pridobivali podatke za analizo. Algoritem smo testirali na dveh kolesarjih v časovnem obdobju enega tedna. S prejetimi asociacijskimi pravili smo lahko primerjali analize voženj obeh kolesarjev.
Keywords:
Apriori
,
Kolesarstvo
,
Strukturirani treningi
,
Analiza voženj
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[D. Krajnc]
Year of publishing:
2021
Number of pages:
VI, 43 str.
PID:
20.500.12556/DKUM-80144
UDC:
004.8(043.2)
COBISS.SI-ID:
94972419
Publication date in DKUM:
18.10.2021
Views:
1007
Downloads:
86
Metadata:
Categories:
KTFMB - FERI
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
31.08.2021
Secondary language
Language:
English
Title:
Mobile application for cycling training analysis
Abstract:
The main goal of this diploma was to develop an application for the analysis of cycling activities and cyclist well-being throughout the day with the Apriori algorithm and association rules. The data was obtained from a bicycle computer and a smartwatch, which was stored in a database and later used for the analysis. The algorithm was tested on two cyclists over a period of one week. We were able to compare the analyses of the rides of both cyclists with the obtained association rules.
Keywords:
Apriori
,
Cycling
,
Structured training
,
Ride analysis
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