Liwei Sun. Fuzzy Evaluation of Athletes’ Movement Ability Based on Convolutional Neural Network. Dynamic Systems and Applications 29 (2020) No. 5, 2041 – 2049

https://doi.org/10.46719/dsa202029538

ABSTRACT.
Participation in modern sports is influenced by various physical, physiological, psychological, and social factors. The main focus in the training process is on the different types of participation in the game and the development of game skills and tactical skills. Usually, it is rarely valued by people, and it has been proved to be a psychological factor in the performance of a higher level of competitive sports. This study aims to measure the ability of athletes and non-athletes to compare various skills with different age groups.  The athlete’s movement ability preparation of the players need the assessment of the various movement skill abilities. To propose a Fuzzy Evaluation based Convolutional Neural Network (FE-CNN) method to Pattern classification is defined as a design method to match the athletic movement input of an output class with a map. The athlete’s skills extract function from the input data or pattern, and these main features are provided to the FE-CNN for subsequent classification. In this proposed method, the athlete’s movement ability classification applied different groups that provide higher performance compared to the existing classification algorithm.

Keywords: Fuzzy Evaluation based Convolutional Neural Network, Athlete’s Movement.