- Tytuł:
- Predicting Competitive Swimming Performance
- Autorzy:
-
Wilk, Robert
Fidos- Czuba, Olga
Rutkowski, Łukasz
Kozłowski, Krzysztof
Wiśniewski, Piotr
Maszczyk, Adam
Stanula, Arkadiusz
Roczniok, Robert - Powiązania:
- https://bibliotekanauki.pl/articles/1055083.pdf
- Data publikacji:
- 2015
- Wydawca:
- Uniwersytet Szczeciński. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego
- Tematy:
-
Kohonen feature map
regression
sports selection
swimming performance - Opis:
- The aim of this study was to present the results of analyses conducted by means of complementary analytic tools in order to verify their efficacy and the hypothesis that Kohonen’s neural models may be applied in the classification process of swimmers. A group of 40 swimmers, aged 23 ±5 years took part in this research. For the purpose of verification of usefulness of Kohonen’s neural models, statistical analyses were carried out on the basis of results of the independent variables (physiological and physical profiles, specific tests in the water). In predicting the value of variables measured with the so called strong scale regression models, numerous variables were used. The construction of such models required strict determination of the endogenous variable (Y – results for swim distances of 200 m crawl), as well as the proper choice of variables in explaining the study’s phenomenon. The optimum choice of explanatory variables for the Kohonen’s networks was made on the grounds of regression analysis. During statistical analysis of the gathered material neural networks were used: Kohonen’s feature maps (data mining analysis). The obtained model has the form of a topological map, where certain areas can be separated, and the map constructed in this way can be used in the assessment of candidates for sports training.
- Źródło:
-
Central European Journal of Sport Sciences and Medicine; 2015, 9, 1; 105-112
2300-9705
2353-2807 - Pojawia się w:
- Central European Journal of Sport Sciences and Medicine
- Dostawca treści:
- Biblioteka Nauki
Artykuł