20.500.12556/DKUM-74361 Primerjava metod za avtomatsko načrtovanje športnih treningov magistrsko delo A comparison of methods for automatic planning of sport training sessions Ljudje imamo izjemno sposobnost za tek, ki ima na naš organizem tako s psihičnega kot fizičnega vidika blagodejne učinke. Vendar se v sodobnem svetu vse bolj pojavlja problem telesne neaktivnosti in pomanjkanja motivacije. Vzroki so različni, med pomembnejšimi je pomanjkanje znanja o učinkovitem pristopu k športnemu treniranju. Učinkovitega športnega treniranja se lahko lotimo s pomočjo rešitev, ki temeljijo na računski inteligenci. V magistrskem delu smo poiskali in pregledali obstoječe metode, ki omogočajo avtomatsko načrtovanje športnih treningov. Izbrane metode smo med seboj primerjali. Na podlagi primerjave smo izbrali eno obstoječo metodo, jo modificirali in implementirali. Končni rezultat je bil uspešno generiran tekaški športni trening. We humans have an exceptional ability to run, which has beneficial effects on our body, both psychologically and physically. However, in today's world there is a growing problem of physical inactivity and lack of motivation. The causes are different. One of them is a lack of knowledge of an effective approach to sports training. Effective sports training can be addressed through computational intelligence-based solutions. In the master's thesis we therefore searched for and reviewed the existing methods that enable automatic planning of sports training. Then we made a comparison of the selected methods. Based on the comparison, we selected one existing method, we modified and implemented it. The result was successfully generated running sports training. avtomatsko načrtovanje računska inteligenca športni trening tek automatic planning computational intelligence sports training running true true false [T. Gašić] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2019-08-25 21:17:20 2019-11-11 14:39:03 2022-08-09 08:59:15 2019-12-10 08:03:31 2019 0 Maribor 0 Maribor XI, 81 str. 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8(043.2) 22828054 URN:SI:UM:DK:HEDSRWVN MAG_Gasic_Tara_2019.pdf MAG_Gasic_Tara_2019.pdf 1 D7AA1FCEFDCC618B87F882DCF0D51AC3 715991b435b10e01689ef8bc3f119191bef94482ab8f69e8aa91e491c0f7d001 d93391a1-7c10-11eb-bb7a-00155d0001ca 20.500.12556/dkum/608c0e85-7066-4efa-9011-5105fa4da5d3 https://dk.um.si/Dokument.php?lang=slv&id=136346 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0