摘要
鉴于研究基础、地域差异及对健康评价的不同视角,国际体质评价指标体系测试指标存在较大差异。我国传统的青少年体质测定采用既定的身体形态机能素质分类标准,缺乏全面、动态的体质状况综合反映。文章采用人工神经网络无监督聚类方法,通过建立基于人工神经网络无监督聚类方法的青少年体质综合评价模型,规避了传统阈值设置的经验型和随意性,找到各测试样本之间的数据联系并确定各项指标的阈值,最终建立科学的青少年体质健康综合评价模型,弥补了原有研究方法和评价模型的不足。
In view of the research foundation,geographical differences and different perspectives of health evaluation,there are great differences in the test indices of international physical condition evaluation index system.In our country,the traditional teenagers’physical condition measurement adopts the established classification standard of body shape and function quality,and lacks comprehensive and dynamic comprehensive reaction of physical condition.In this paper,the artificial neural network unsupervised clustering method is adopted.Through establishing the comprehensive evaluation model of teenagers’physical condition based on the artificial neural network unsupervised clustering method,the empirical type and arbitrariness of the traditional threshold setting are avoided,the data links of each test sample are found and the thresholds of each index are determined,finally the scientific comprehensive evaluation model of teenagers’physical condition is established,which makes up the deficiency of the original research method and evaluation model.
作者
乐妍
Le Yan(Chengdu Sport University,Chengdu 610041,China)
出处
《江苏科技信息》
2020年第33期76-79,共4页
Jiangsu Science and Technology Information
关键词
神经网络
聚类
体质评价
模型研究
neural network
clustering
physical condition evaluation
model research