基于体质测试大数据的灰色关联分析:建模与实证

Grey Relational Analysis Based on Big Data of Physical Fitness Test:Modeling and Demonstration

目前,中国普遍采用电子仪器采集学生体质测试结果,积累了大量具有大数据特征的原始数据。在面对体质测试大数据时,如何利用数学模型找出测试项目之间的相关性,从而准确描述其相关性的强弱,具有科学意义。采用改进的灰色关联分析模型,对西部某高校31198名大学生体质测试大数据进行分析。该模型改变了传统邓氏模型的计算过程,使其适用于大数据。结果表明:BMI值对女生下肢耐力和爆发力有较大影响,是女生最重要的体质测试指标;肺活量对男生的耐力、灵活性和下肢爆发力有不同的影响,是男生最重要的体质测试指标;长跑,即男子1000 m跑、女子800 m跑和立定跳远,不仅是身体素质的2个最重要的指标,而且它们之间存在着很强的相关性。改进的灰色关联分析为大数据环境下体质测量指标之间的相关性分析提供了新的思路,为不同领域的大数据分析提供了建模参考。

At present,the electronic instruments have been generally utilized to collect the test results of physical fitness of students in China,and we have accumulated a lot of raw data which have characteristics of big data.It may have scientific significance on how to utilize the mathematical model in finding out the correlations among the test items when facing test big data of physical fitness and then describing accurately the strength and weakness of their correlations.In this study,we utilized an innovative model of grey relational analysis in order to analyze the test big data of physical fitness of the 31198 undergraduate students in a university in western China.The innovative model changes the computational process of traditional Deng’s model and then makes itself suitable for big data.The value of BMI has a great influence on the endurance and the explosive force of lower limbs of the female students,and it is the most important test index of females’physical fitness;The vital capacity has different influence on the endurance,the flexibility and the explosive force of lower limbs of the male students,and it is the most important test index of male physical fitness;long-distance running that is the 1000-meter running for males as well as the 800-meter running for females and the standing long jump are not only the two most important indicators of the physical fitness but also exist a strong correlation among them.The innovative model of Grey Relational Analysis provides a new idea for the correlation analysis among the physical measurement indexes under the situation of big data,and it gives a modeling reference for the big data analysis in different fields.