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Title:
SESTAVLJANJE URNIKA S POMOČJO ROJNE INTELIGENCE NA MOBILNI PLATFORMI ANDROID
Authors:
ID
Merc, Leon
(Author)
ID
Fister, Iztok
(Mentor)
More about this mentor...
Files:
UNI_Merc_Leon_2013.pdf
(1,92 MB)
MD5: 7B96B39944D541F0C8601EC351B87F2C
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V diplomski nalogi se ukvarjamo s problemom avtomatizirane generacije urnika za poljubno šolsko ustanovo. Kot ciljni operacijski sistem smo uporabili mobilno platformo Android. Za optimizacijo samega urnika smo uporabili pristop rojne inteligence, natančneje algoritma PSO (angl. Particle swarm optimization), katerega smo tudi podrobno opisali. Ugotovili smo, da je optimizacija z zadovoljivimi rezultati na mobilnem telefonu možna, ter predstavili pridobljene rezultate pri različnih konstantah.
Keywords:
Android
,
rojna inteligenca
,
optimizacija z roji delcev
Place of publishing:
Maribor
Publisher:
[L. Merc]
Year of publishing:
2013
PID:
20.500.12556/DKUM-42268
UDC:
004.89:621.395.72(043.2)
COBISS.SI-ID:
17485846
NUK URN:
URN:SI:UM:DK:UBG6DNLM
Publication date in DKUM:
20.09.2013
Views:
2068
Downloads:
164
Metadata:
Categories:
KTFMB - FERI
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:
MERC, Leon, 2013,
SESTAVLJANJE URNIKA S POMOČJO ROJNE INTELIGENCE NA MOBILNI PLATFORMI ANDROID
[online]. Bachelor’s thesis. Maribor : L. Merc. [Accessed 28 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=42268
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Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.
Secondary language
Language:
English
Title:
TIMETABELING USING SWARM INTELLIGENCE ON MOBILE PLATFORM ANDROID
Abstract:
In the thesis, we have dealt with the problem of automatic timetable generation for a chosen academic institution. As the target operating system, an Android mobile platform was used. The swarm intelligence approach, specifically the PSO (Particle swarm Optimization) algorithm was applied for scheduling the optimization itself. This algorithm is also described in detail. The conclusion of this thesis is that the automatic generation of timetable on mobile devices is possible and the obtained results are appropriate to use in a real-world.
Keywords:
Android
,
swarm intelligence
,
Particle Swarm Optimization
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