基于K-means聚类和BP神经网络的大学生体质类型评价模型  

Evaluation Model of College Students'Physique Type Based on K-means Clustering and BP Neural Network

作　　者：郝霖霖 HAO Linlin(Department of Physical Education,Fudan University,Shanghai,200433 China)

机构地区：[1]复旦大学体教部,上海200433

出　　处：《当代体育科技》2021年第32期1-8,共8页Contemporary Sports Technology

基　　金：教育部人文社会科学研究(18YJC890007)。

摘　　要：该文利用K-means聚类算法和BP神经网络对大学生体质类型进行评价,验证BP神经网络评价大学生体质类型的可行性。K-means聚类分析结果表明,大学男生和女生体质均可分为八类,不同类型具有不同的体质特点。利用聚类分析数据训练BP神经网络,建立体质评价模型,其精确度达到94%以上,能够较为准确地判断大学生的体质类型,可以作为自动化、精准化评价大学生体质类型的基础算法。In this paper,K-means clustering algorithm and BP neural network are used to evaluate the physique types of college students,and to verify the feasibility of BP neural network to evaluate the physique types of college students.The results of K-means cluster analysis show that the physique of male college students can be divided into eight categories,and that of female college students can be divided into eight categories.Different types have different physical characteristics.The BP neural network is trained by clustering analysis data,and the fitness evaluation model is established.The accuracy is more than 94%,which can be used as the basic algorithm for automatic and accurate evaluation of college students'fitness type.

关 键 词：大学生体质评价 BP 神经网络 大学生体育锻炼 K-MEANS 聚类 

分 类 号：G8[文化科学—体育学]