The application of support vector machine in classifying potential archers using bio-mechanical indicators

Zahari, Taha and Musa, Rabiu Muazu and Anwar, P. P. Abdul Majeed and Mohamad Razali, Abdullah and Muhammad Amirul, Abdullah and M. H. A., Hassan (2018) The application of support vector machine in classifying potential archers using bio-mechanical indicators. In: Intelligent Manufacturing & Mechatronics: Proceedings of Symposium, 29 January 2018, Pekan, Pahang, Malaysia. Lecture Notes in Mechanical Engineering . Springer Singapore, Singapore, pp. 385-391. ISBN 9789811087875

Preview	Pdf The Application of Support Vector Machine in-fkp-2018-1.pdf Download (126kB) | Preview
	Pdf book47 The application of support vector machine in classifying potential archers using bio-mechanical indicators.pdf Restricted to Repository staff only Download (372kB) | Request a copy

Abstract

This study classifies potential archers from a set of bio-mechanical indicators trained via different Support Vector Machine (SVM) models. 50 youth archers drawn from a number of archery programmes completed a one end archery shooting score test. Bio-mechanical evaluation of postural sway, bow movement, muscles activation of flexor and extensor as well as static balance were recorded. k-means clustering technique was used to cluster the archers based on the indicators tested. Fine, medium and coarse radial basis function kernel-based SVM models were trained based on the measured indicators. The five-fold cross-validation technique was utilised in the present investigation. It was shown from the present study, that the employment of SVM is able to assist coaches in identifying potential athletes in the sport of archery.

Item Type:	Book Chapter
Uncontrolled Keywords:	Bio-mechanical Indicators; Artificial Intelligence; Classification; Support; Vector; Machine
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Faculty of Manufacturing Engineering
Depositing User:	Dr. Mohd Hasnun Arif Hassan
Date Deposited:	28 May 2018 06:32
Last Modified:	07 Aug 2018 04:20
URI:	http://umpir.ump.edu.my/id/eprint/21162
Download Statistic:	View Download Statistics

Actions (login required)

View Item