Machine learning in sports [electronic resource] : identifying potential archers / by Rabiu Muazu Musa ... [et al.].
- 其他作者：
- 其他題名：
- SpringerBriefs in applied sciences and technology.
- 出版： Singapore : Springer Singapore :Imprint: Springer 2019.
- 叢書名： SpringerBriefs in applied sciences and technology,
- 主題： Archery. , Machine learning. , Performance--Measurement. , Computational Intelligence. , Sport. , Simulation and Modeling. , Sport Psychology. , Biomedical Engineering and Bioengineering. , Computer Appl. in Social and Behavioral Sciences.
- ISBN： 9789811325922 (electronic bk.) 、 9789811325915 (paper)
- URL：
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電子書(校內)
- 一般註：E1084學校採購電子書 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.
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讀者標籤：
- 系統號： 000274312 | 機讀編目格式
館藏資訊
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.
摘要註
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.