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

cris.lastimport.scopus2026-02-26T16:02:23Z
dc.contributorNational Taiwan University of Sport
dc.creatorLiu, Jing-Wei
dc.creatorChen, Sheng-Hsiang
dc.creatorChen, Che-Hsiu
dc.creatorHuang, Tsung-Han
dc.date2021-07
dc.date.accessioned2021-10-30T05:05:40Z
dc.date.accessioned2025-07-28T15:13:29Z
dc.date.available2021-10-30T05:05:40Z
dc.date.issued2021-10-30T05:05:40Z
dc.description.abstractTaiwan'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.
dc.format.extent126 bytes
dc.format.mimetypetext/html
dc.identifier.doi10.1007/s00500-021-06050-3
dc.identifier.issn1432-7643
dc.identifier.urihttps://ir.ntus.edu.tw/handle/987654321/65805
dc.languageen_US
dc.publisherNew York: SPRINGER
dc.relationSOFT COMPUTING
dc.subjectArtificial intelligence
dc.subjectAHP
dc.subjectTOPSIS
dc.subjectRowing
dc.titleConstructing an artificial intelligence strategy algorithm for the identification of talented rowing athletes
dc.typearticle
dspace.entity.typePublication

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