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1860796911143878656
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INTELEK Repository
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Online Access
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https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2021-03-22 00:41:49
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Restricted Document
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| id |
10652
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UniSZA
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4719-01-FH05-ESERI-21-51623.pdf
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Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML
like Gecko) Chrome/88.0.4324.190 Safari/537.36
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10652
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10652 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10652 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Book Chapter application/pdf 4 1.6 Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/88.0.4324.190 Safari/537.36 Skia/PDF m88 2021-03-22 00:41:49 4719-01-FH05-ESERI-21-51623.pdf UniSZA Private Access Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer The success of a given elite beach soccer team is identified through a number of technical and tactical performance indicators in this chapter. The demarcation of the winning and losing team was determined through the use of the Louvain clustering technique. Subsequently, a number of artificial neural network (ANN) models were developed by varying different hyperparameters in evaluating its ability to accurately ascertaining the class of a team. It was shown from the study that through the framework provided, the best ANN architecture, as well as performance indicators identified, could yield an average classification accuracy of 92.5% on the validation and test dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 Springer Springer 21-28 SpringerBriefs in Applied Sciences and Technology
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| spellingShingle |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
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| summary |
The success of a given elite beach soccer team is identified through a number of technical and tactical performance indicators in this chapter. The demarcation of the winning and losing team was determined through the use of the Louvain clustering technique. Subsequently, a number of artificial neural network (ANN) models were developed by varying different hyperparameters in evaluating its ability to accurately ascertaining the class of a team. It was shown from the study that through the framework provided, the best ANN architecture, as well as performance indicators identified, could yield an average classification accuracy of 92.5% on the validation and test dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020
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| title |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
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| title_full |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
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| title_fullStr |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
|
| title_full_unstemmed |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
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| title_short |
Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
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| title_sort |
technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer
|