Authors
Yasunori Takemura1, *, Kazuya Oda2, Michiyoshi Ono1
1
Department of Engineering, Nishinippon Institute of Technology, Miyako, Fukuoka 800-0344, Japan
2
Department of Life Science and System Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 808-0896, Japan
*
Corresponding author. Email: [email protected]
Corresponding Author
Yasunori Takemura
Received 9 April 2018, Accepted 15 November 2018, Available Online 1 December 2018.
DOI
https://doi.org/10.2991/jrnal.2018.5.3.12How to use a DOI?
Keywords
Sports science; SOM; machine learning; clustering
Abstract
In Japan, sports efforts are actively being carried out to host the 2020 Olympic Games. Especially in the field of sports science, researches on ergonomics, development of sports equipment and pattern recognition technology using artificial intelligence are actively researched. In previous research, we developed a clustering algorithm for positioning adaptation and relationships in team sports using self-organizing maps in university rugby players. However, I have not yet confirmed whether the developed algorithm can be applied to other team sports. For this reason, we applied the same algorithm to a university volleyball player. Then, as an algorithm, we verify whether it can be generally used for team sports.

Copyright
© 2018 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).