The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach

Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. The present study classified and predicted high and low potential archers from a collection of...

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Main Authors:	Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah, Muhammad Aizzat, Zakaria, Muhammad Muaz, Alim, Jessnor Arif, Mat Jizat, Mohamad Fauzi, Ibrahim
Format:	Conference or Workshop Item
Language:	English
Published:	IOP Publishing 2018
Subjects:	TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/21837/ http://umpir.ump.edu.my/id/eprint/21837/ http://umpir.ump.edu.my/id/eprint/21837/1/The%20identification%20of%20high%20potential%20archers%20based%20on%20relative%20psychological%20coping%20skills%20variables.pdf

id	ump-21837
recordtype	eprints
spelling	ump-218372018-09-25T04:11:55Z http://umpir.ump.edu.my/id/eprint/21837/ The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach Zahari, Taha Rabiu Muazu, Musa Anwar, P. P. Abdul Majeed Mohamad Razali, Abdullah Muhammad Aizzat, Zakaria Muhammad Muaz, Alim Jessnor Arif, Mat Jizat Mohamad Fauzi, Ibrahim TS Manufactures Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. The present study classified and predicted high and low potential archers from a collection of psychological coping skills variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. Psychological coping skills inventory which evaluates the archers level of related coping skills were filled out by the archers prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. SVM models, i.e. linear and fine radial basis function (RBF) kernel functions, were trained on the psychological variables. The k-means clustered the archers into high psychologically prepared archers (HPPA) and low psychologically prepared archers (LPPA), respectively. It was demonstrated that the linear SVM exhibited good accuracy and precision throughout the exercise with an accuracy of 92% and considerably fewer error rate for the prediction of the HPPA and the LPPA as compared to the fine RBF SVM. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected psychological coping skills variables examined which would consequently save time and energy during talent identification and development programme. IOP Publishing 2018 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/21837/1/The%20identification%20of%20high%20potential%20archers%20based%20on%20relative%20psychological%20coping%20skills%20variables.pdf Zahari, Taha and Rabiu Muazu, Musa and Anwar, P. P. Abdul Majeed and Mohamad Razali, Abdullah and Muhammad Aizzat, Zakaria and Muhammad Muaz, Alim and Jessnor Arif, Mat Jizat and Mohamad Fauzi, Ibrahim (2018) The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach. In: 4th Asia Pacific Conference on Manufacturing Systems and the 3rd International Manufacturing Engineering Conference, APCOMS-iMEC 2017, 7-8 December 2017 , Yogyakarta, Indonesia. pp. 1-6., 319. doi:10.1088/1757-899X/319/1/012027
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TS Manufactures
spellingShingle	TS Manufactures Zahari, Taha Rabiu Muazu, Musa Anwar, P. P. Abdul Majeed Mohamad Razali, Abdullah Muhammad Aizzat, Zakaria Muhammad Muaz, Alim Jessnor Arif, Mat Jizat Mohamad Fauzi, Ibrahim The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
description	Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. The present study classified and predicted high and low potential archers from a collection of psychological coping skills variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. Psychological coping skills inventory which evaluates the archers level of related coping skills were filled out by the archers prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. SVM models, i.e. linear and fine radial basis function (RBF) kernel functions, were trained on the psychological variables. The k-means clustered the archers into high psychologically prepared archers (HPPA) and low psychologically prepared archers (LPPA), respectively. It was demonstrated that the linear SVM exhibited good accuracy and precision throughout the exercise with an accuracy of 92% and considerably fewer error rate for the prediction of the HPPA and the LPPA as compared to the fine RBF SVM. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected psychological coping skills variables examined which would consequently save time and energy during talent identification and development programme.
format	Conference or Workshop Item
author	Zahari, Taha Rabiu Muazu, Musa Anwar, P. P. Abdul Majeed Mohamad Razali, Abdullah Muhammad Aizzat, Zakaria Muhammad Muaz, Alim Jessnor Arif, Mat Jizat Mohamad Fauzi, Ibrahim
author_facet	Zahari, Taha Rabiu Muazu, Musa Anwar, P. P. Abdul Majeed Mohamad Razali, Abdullah Muhammad Aizzat, Zakaria Muhammad Muaz, Alim Jessnor Arif, Mat Jizat Mohamad Fauzi, Ibrahim
author_sort	Zahari, Taha
title	The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
title_short	The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
title_full	The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
title_fullStr	The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
title_full_unstemmed	The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
title_sort	identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach
publisher	IOP Publishing
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/21837/ http://umpir.ump.edu.my/id/eprint/21837/ http://umpir.ump.edu.my/id/eprint/21837/1/The%20identification%20of%20high%20potential%20archers%20based%20on%20relative%20psychological%20coping%20skills%20variables.pdf
first_indexed	2023-09-18T22:32:13Z
last_indexed	2023-09-18T22:32:13Z
_version_	1777416361257992192

The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach

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