國立虎尾科技大學 |

Machine Learning in Sports = Identifying Potential Archers /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine Learning in Sports/ by Rabiu Muazu Musa, Zahari Taha, Anwar P.P.Abdul Majeed, Mohamad Razali Abdullah.
Reminder of title:	Identifying Potential Archers /
Author:	Muazu Musa, Rabiu.
other author:	Taha, Zahari.
Description:	XII, 45 p. 11 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-981-13-2592-2
ISBN:	9789811325922

Machine Learning in Sports = Identifying Potential Archers /
Muazu Musa, Rabiu.

Machine Learning in SportsIdentifying Potential Archers /[electronic resource] :by Rabiu Muazu Musa, Zahari Taha, Anwar P.P.Abdul Majeed, Mohamad Razali Abdullah. - 1st ed. 2019. - XII, 45 p. 11 illus. in color.online resource. - SpringerBriefs in Applied Sciences and Technology,2191-530X. - SpringerBriefs in Applied Sciences and Technology,.

Introduction -- Bio-physiological indicators in evaluating archery performance -- Psychological variables in ascertaining potential archers -- Anthropometry correlation to archery performance -- Physical fitness parameters in the identification of high potential archers -- Concluding remarks.

This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.

ISBN: 9789811325922

Standard No.: 10.1007/978-981-13-2592-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Machine Learning in Sports = Identifying Potential Archers /
LDR:02571nam a22003975i 4500 001 1016074
003 DE-He213
005 20200629151242.0
007 cr nn 008mamaa
008 210106s2019 si | s |||| 0|eng d
020 $a 9789811325922 $9 978-981-13-2592-2
024 7 $a 10.1007/978-981-13-2592-2 $2 doi
035 $a 978-981-13-2592-2
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Muazu Musa, Rabiu. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1310400
245 1 0 $a Machine Learning in Sports $h [electronic resource] : $b Identifying Potential Archers / $c by Rabiu Muazu Musa, Zahari Taha, Anwar P.P.Abdul Majeed, Mohamad Razali Abdullah.
250 $a 1st ed. 2019.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a XII, 45 p. 11 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Applied Sciences and Technology, $x 2191-530X
505 0 $a Introduction -- Bio-physiological indicators in evaluating archery performance -- Psychological variables in ascertaining potential archers -- Anthropometry correlation to archery performance -- Physical fitness parameters in the identification of high potential archers -- Concluding remarks.
520 $a This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.
650 0 $a Computational intelligence. $3 568984
650 0 $a Sports. $3 584007
650 0 $a Computer simulation. $3 560190
650 0 $a Sports—Psychological aspects. $3 1259593
650 0 $a Biomedical engineering. $3 588770
650 0 $a Application software. $3 528147
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Sport. $2 gtt $3 790024
650 2 4 $a Simulation and Modeling. $3 669249
650 2 4 $a Sport Psychology. $3 1115203
650 2 4 $a Biomedical Engineering and Bioengineering. $3 1211019
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 669920
700 1 $a Taha, Zahari. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1283527
700 1 $a P.P.Abdul Majeed, Anwar. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1310401
700 1 $a Abdullah, Mohamad Razali. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1310402
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811325915
776 0 8 $i Printed edition: $z 9789811325939
830 0 $a SpringerBriefs in Applied Sciences and Technology, $x 2191-530X $3 1253575
856 4 0 $u https://doi.org/10.1007/978-981-13-2592-2
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)