rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Machine Learning in Sports
    sub title: Identifying Potential Archers
  name:
    name part: Muazu Musa, Rabiu.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Taha, Zahari.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: P.P.Abdul Majeed, Anwar.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Abdullah, Mohamad Razali.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 45 p. 11 illus. in color. online resource.
  abstract: 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.
  table of contents: 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.
  note: by Rabiu Muazu Musa, Zahari Taha, Anwar P.P.Abdul Majeed, Mohamad Razali Abdullah.
  subject:
    topic: Computational intelligence
  subject:
    topic: Sports
  subject:
    topic: Computer simulation
  subject:
    topic: Sports-Psychological aspects
  subject:
    topic: Biomedical engineering
  subject:
    topic: Application software
  subject:
    topic: Computational Intelligence
  subject:
    topic: Sport
  subject:
    topic: Simulation and Modeling
  subject:
    topic: Sport Psychology
  subject:
    topic: Biomedical Engineering and Bioengineering
  subject:
    topic: Computer Appl. in Social and Behavioral Sciences
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Applied Sciences and Technology
  identifier: 9789811325922
  identifier: https://doi.org/10.1007/978-981-13-2592-2
  record info:
    record creation date: 181107
    record change date: 20191023132950.0
    record identifier: 978-981-13-2592-2