Application of fuzzy modeling to rowing motion analysis

Kanta Tachibana*, Takeshi Furuhashi, Manabu Shimoda, Yasuo Kawakami, Tetsuo Fukunaga


研究成果: Conference article査読

1 被引用数 (Scopus)


Fuzzy modeling has distinct features, which are applicability to nonlinear systems and ability to extract knowledge. Fuzzy neural network (FNN) enables automatic acquisition of knowledge. The authors have proposed an uneven division of input space for the FNN which reduces the number of fuzzy rules without sacrificing the precision of the model. In many sports, nonlinear factors affect the performance. In rowing competitions, the performance criterion is the boat speed. In this paper, fuzzy modeling is applied to reveal the relationships between the supplied power and the boat speed. The forces and the angles of on-water rowing are measured. The subjects are candidates of Japanese national team members. The total propulsive work, consistency and uniformity of the propulsive power were calculated from the force and the angle data. The relationships between these factors and the performance were identified with fuzzy modeling. Comparing to linear regression, more precise and more comprehensive model was obtained.

ページ(範囲)VI-190 - VI-195
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
出版ステータスPublished - 1999
イベント1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
継続期間: 1999 10月 121999 10月 15

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ハードウェアとアーキテクチャ


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