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

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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.

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Funding

The authors did not receive support from any organization for the submitted work.

Author information

Authors and Affiliations

  1. Department of Sport Information and Communication, National Taiwan University of Sport, Taichung, Taiwan

    Jing-Wei Liu & Sheng-Hsiang Chen

  2. Department of Sport Performance, National Taiwan University of Sport, Taichung, Taiwan

    Che-Hsiu Chen

  3. Graduate Institute of Recreational Sport Management, National Taiwan University of Sport, Taichung, Taiwan

    Tsung-Han Huang

Authors
  1. Jing-Wei Liu
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  2. Sheng-Hsiang Chen
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  3. Che-Hsiu Chen
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  4. Tsung-Han Huang
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Contributions

Jing-Wei Liu contributed to writing—original draft, conceptualization, constructing experimental model, and methodology. Sheng-Hsiang Chen contributed to methodology, validation, and writing—review and editing. Che-Hsiu Chen contributed to data curation. Tsung-Han Huang contributed to project administration and data curation.

Corresponding author

Correspondence to Sheng-Hsiang Chen.

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The authors declare that they have no obvious competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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This article does not present any studies with human participants or animals performed by any of the authors.

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Communicated by Mu-Yen Chen.

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Liu, JW., Chen, SH., Chen, CH. et al. Constructing an artificial intelligence strategy algorithm for the identification of talented rowing athletes. Soft Comput 27, 1743–1750 (2023). https://doi.org/10.1007/s00500-021-06050-3

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