摘要
论文将神经网络和判别函数引入对羽毛球运动员的技能水平评估,并使用这两种方法对基于视觉识别测试数据进行羽毛球运动员技能水平的分类。被分类为高级水平、中级技能水平或初级水平的41名参与者参加了这项测试。结果表明与判别函数分析相比,神经网络在水平评估方面更为有效,分类的准确度更高。使用测试结果,结合参与者的人体生理指标和运动适应性参数,对基于视觉识别的评估程序的有效性和准确性进行验证,并提出了将基于视觉的训练方法引入羽毛球运动员训练计划的思路。
In this paper,the neural network and discriminant function are introduced to evaluate the skill level of badminton players,and these two methods are used to classify the badminton player skill level based on the visual identification test data.The 41 participants classified as Advanced,Intermediate and Beginner Skill participated in the test.The results show that compared with the discriminant function analysis,the neural network is more effective in the level assessment and the classification accuracy is higher.The validity and accuracy of the appraisal procedure based on visual recognition are verified by using the test results,combined with the participants'human physiological indices and motor adaptability parameters,and the idea of introducing the visual-based training method into the badminton player training program is put forward.
作者
王晓
WANG Xiao(Xi'an Aviation Polytechnic,Xi'an 710089)
出处
《计算机与数字工程》
2018年第7期1311-1315,1472,共6页
Computer & Digital Engineering
关键词
技能水平评估
羽毛球
神经网络
判别函数
视觉识别
skill level assessment
badminton
neural network
discriminant function
visual recognition
