Machine Learning in Sports : Identifying Potential Archers / by Rabiu Muazu Musa, Zahari Taha, Anwar P.P.Abdul Majeed, Mohamad Razali Abdullah.
By: Muazu Musa, Rabiu, autor
Contributor(s): SpringerLink (Online service)
| Taha, Zahari., autor | P.P.Abdul Majeed, Anwar., autor | Abdullah, Mohamad Razali., autor
Series: (SpringerBriefs in Applied Sciences and Technology, 2191-530X); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Singapore : Springer Singapore : Imprint: Springer, 2019Description: 1 recurso en línea (XII, 45 páginas) : 11 ilustraciones a color.ISBN: 9789811325922.Subject: Tiro con arco
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | GV1185 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks26062092 |
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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.
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