Repository logo
  • English
  • 中文
  • Log In
    Have you forgotten your password?
Repository logo
    Communities & Collections
    Research Outputs
    Fundings & Projects
    People
    Organizations
    Statistics
  • English
  • 中文
  • Log In
    Have you forgotten your password?
  1. Home
  2. 運動產業學院
  3. 運動資訊與傳播學系
  4. 期刊論文
  5. Constructing an artificial intelligence strategy algorithm for the identification of talented rowing athletes
 
  • Details
Options

Constructing an artificial intelligence strategy algorithm for the identification of talented rowing athletes

Journal Volume
27
Journal Issue
3
Start Page
1743
End Page
1750
Date Issued
2023
Author(s)
劉經緯  
運動資訊與傳播學系  
陳聖翔  
運動資訊與傳播學系  
陳哲修  
競技運動學系  
Huang, Tsung-Han
DOI
https://doi.org/10.1007/s00500-021-06050-3
URI
https://ir.ntus.edu.tw/handle/123456789/131450
Abstract
Taiwan’s rowing athletes have performed well during the Asian Games, but their performance in the Olympics has not been adequate. In addition to their hard work and rigorous and effective training, the skill of the athletes is a key factor for achieving good results. In this study, an artificial intelligence (AI) evaluation algorithm is developed to help rowing athletes excel in the sporting events. The AI algorithm uses the analytic hierarchy process to invite experts and scholars in the rowing field to answer a questionnaire. The technique for order performance by similarity to ideal solution is then applied to calculate the ranking of selection indicators, to construct an evaluation model for rowing athletes. The key findings indicate that physicality (or the body structure) is the highest priority among the four main aspects of talent identification; this is followed, in descending order, by specialism, reaction, and psychological elements. The proposed AI strategy was established as the most beneficial decision model and can be used to identify talented rowers in the future.
Publisher
Soft Computing
Type
journal article
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback