摘要
传统的基于《国家学生体质健康标准》的体质评价方法以固定分值和等级反映学生体质健康状况,便于大范围数据比较,但类别划分过于死板。云模型用期望值、熵和超熵三个数值来表征定性概念的模糊性和随机性,便于揭示不确定性的普遍规律。用正态云进行的学生体质状况分析具有方法直观、使用灵活、易于揭示小范围数据的突出特点等优点,是一种有效的抽样数据分析方法。
The traditional student physical evaluation approach based on ＂National Students Health Standard＂ reflects student＇ s health status with fixed physical evaluation scores and grades, which facilitates a wide range of data comparison, but the categories are too rigid. Cloud model uses the expected Value, entropy and hyper entropy three values to characterize the ambiguity and randomness of the concept of qualitative, to easily reveal the universal law of uncertainty. Student＇ s health status evaluation carried out with the normal cloud model approach is an effective method of sampling data analysis, which has merits of intuitive, flexible, and easy - to reveal the salient features of small-scale data, etc.
出处
《科学技术与工程》
2010年第7期1777-1780,共4页
Science Technology and Engineering
基金
国家社会科学基金资助项目(06BYY047)
河南省教育厅2008年自然科学研究项目(2008A520020)资助
关键词
云模型
体质
正态云
熵
模糊
cloud model physical condition normal cloud entropy ambiguity
