Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques

Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques

The present study aims to explore different physical characteristics towards a successful performance of archery and to predict the most vital attributes that contribute to the achievement of high archery scores. 32 archers drawn from different archery programmes participated in the study. Standard...

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Main Authors: Zahari, Taha, Haque, Mainul, Musa, Rabiu Muazu, Mohamad Razali, Abdullah, Maliki, Ahmad Bisyri Husin Musawi, Norzulaika, Alias, Norlaila Azura, Kosni
Format: Article
Language:English
Published: Publication Ethics 2017
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/18385/
http://umpir.ump.edu.my/id/eprint/18385/
http://umpir.ump.edu.my/id/eprint/18385/1/Intelligent%20Prediction%20of%20Suitable%20Physical%20Characteristics%20Toward%20Archery%20Performance%20Using%20Multivariate%20Techniques.pdf
id ump-18385
recordtype eprints
spelling ump-183852018-01-24T02:45:58Z http://umpir.ump.edu.my/id/eprint/18385/ Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques Zahari, Taha Haque, Mainul Musa, Rabiu Muazu Mohamad Razali, Abdullah Maliki, Ahmad Bisyri Husin Musawi Norzulaika, Alias Norlaila Azura, Kosni TS Manufactures The present study aims to explore different physical characteristics towards a successful performance of archery and to predict the most vital attributes that contribute to the achievement of high archery scores. 32 archers drawn from different archery programmes participated in the study. Standard physical characteristics tests were conducted, and archers’ shooting scores of one end were recorded. Multivariate techniques of principal component analysis (PCA), hierarchical agglomerative cluster analysis (HACA) and discriminant analysis (DA) were used to achieve the aims of the study. The PCA after varimax rotation indicates two variables containing 12 and 2 varifacators (VF). The First VF revealing high positive loadings from weight (0.94), calf circumference (cc) (0.89), abdomen cc (0.97), hip cc (0.97), thigh cc (0.95), triceps thickness (0.76), biceps thickness (0.75), subscapular thickness (0.83), suprailiac thickness (0.85), abdominal thickness (0.85), front thigh thickness (0.76) and medial calf thickness (0.80) revealing that endomorphic body positively affect the performance of the sport. The second VF discloses high negative loadings from height (-0.88) and arm length (-0.90) describing that body height, and arm length negatively affects the performance of the sport. HACA classified the archers into three classes based on the PCA outputs namely; High-performance class, Medium-performance class and Low-performance class. Standard, backward and forward stepwise DA discriminate the classes from the 14 predicted variables with accuracies of 74.19%, 96.77% and 93.55% respectively. The findings from the current study can be helpful in mapping out potential athletes in archery based on their physical characteristics. Publication Ethics 2017 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/18385/1/Intelligent%20Prediction%20of%20Suitable%20Physical%20Characteristics%20Toward%20Archery%20Performance%20Using%20Multivariate%20Techniques.pdf Zahari, Taha and Haque, Mainul and Musa, Rabiu Muazu and Mohamad Razali, Abdullah and Maliki, Ahmad Bisyri Husin Musawi and Norzulaika, Alias and Norlaila Azura, Kosni (2017) Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques. Journal of Global Pharma Technology, 9 (7). pp. 44-52. ISSN 0975 -8542 http://jgpt.co.in/index.php/jgpt/article/view/239
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
Haque, Mainul
Musa, Rabiu Muazu
Mohamad Razali, Abdullah
Maliki, Ahmad Bisyri Husin Musawi
Norzulaika, Alias
Norlaila Azura, Kosni
Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
description The present study aims to explore different physical characteristics towards a successful performance of archery and to predict the most vital attributes that contribute to the achievement of high archery scores. 32 archers drawn from different archery programmes participated in the study. Standard physical characteristics tests were conducted, and archers’ shooting scores of one end were recorded. Multivariate techniques of principal component analysis (PCA), hierarchical agglomerative cluster analysis (HACA) and discriminant analysis (DA) were used to achieve the aims of the study. The PCA after varimax rotation indicates two variables containing 12 and 2 varifacators (VF). The First VF revealing high positive loadings from weight (0.94), calf circumference (cc) (0.89), abdomen cc (0.97), hip cc (0.97), thigh cc (0.95), triceps thickness (0.76), biceps thickness (0.75), subscapular thickness (0.83), suprailiac thickness (0.85), abdominal thickness (0.85), front thigh thickness (0.76) and medial calf thickness (0.80) revealing that endomorphic body positively affect the performance of the sport. The second VF discloses high negative loadings from height (-0.88) and arm length (-0.90) describing that body height, and arm length negatively affects the performance of the sport. HACA classified the archers into three classes based on the PCA outputs namely; High-performance class, Medium-performance class and Low-performance class. Standard, backward and forward stepwise DA discriminate the classes from the 14 predicted variables with accuracies of 74.19%, 96.77% and 93.55% respectively. The findings from the current study can be helpful in mapping out potential athletes in archery based on their physical characteristics.
format Article
author Zahari, Taha
Haque, Mainul
Musa, Rabiu Muazu
Mohamad Razali, Abdullah
Maliki, Ahmad Bisyri Husin Musawi
Norzulaika, Alias
Norlaila Azura, Kosni
author_facet Zahari, Taha
Haque, Mainul
Musa, Rabiu Muazu
Mohamad Razali, Abdullah
Maliki, Ahmad Bisyri Husin Musawi
Norzulaika, Alias
Norlaila Azura, Kosni
author_sort Zahari, Taha
title Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
title_short Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
title_full Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
title_fullStr Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
title_full_unstemmed Intelligent Prediction of Suitable Physical Characteristics Toward Archery Performance Using Multivariate Techniques
title_sort intelligent prediction of suitable physical characteristics toward archery performance using multivariate techniques
publisher Publication Ethics
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/18385/
http://umpir.ump.edu.my/id/eprint/18385/
http://umpir.ump.edu.my/id/eprint/18385/1/Intelligent%20Prediction%20of%20Suitable%20Physical%20Characteristics%20Toward%20Archery%20Performance%20Using%20Multivariate%20Techniques.pdf
first_indexed 2023-09-18T22:26:01Z
last_indexed 2023-09-18T22:26:01Z
_version_ 1777415971462447104

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