基于关联规则数据挖掘的大学生体育锻炼行为阶段体质健康知识发现

数据挖掘是大数据时代知识发现的重要手段。通过关联规则数据挖掘,发现不同体育锻炼行为阶段大学生体质健康特征知识。以问卷和体质测试调查法调查在校大学生,构建数据库,以体育锻炼行为阶段为输出、体质指标为输入构建关联规则数据挖掘模型。结果表明,男生预期阶段体质主要表现为心肺机能低下,反应时中等以及双手背勾优;准备阶段心肺机能低下、力量素质和反应时差;行动阶段心肺机能和力量素质差,反应时和柔韧性优;女生前预期阶段力量差、柔韧性好;预期阶段握力及格、背勾优秀、反应时中等以及相对VO2max中等,广泛存在"体重正常的胖子"现象;行动阶段力量差、反应时中等、柔韧性优秀的特征。关联规则数据挖掘能有效发现不同体育锻炼行为阶段大学生体质特征,为大学生体质健康促进提供决策支持。

Discovery of Physical Fitness Knowledges in College Students' Physical Exercise Behavior Based on Association Rule Data Mining

Data mining is an important means of knowledge discovery in the era of big data.To explore the physical health characteristics and stages of physical exercise behavior in college students by association rules of data mining, questionnaire and physical fitness test are used to investigate students at schoolandbuild the database. The data mining model of association rules are constructed with physical exercise behavior stage as the output and physical fitness index as the input.The results indicate that in expected stage of male students are mainly with low cardiopulmonary function, moderate reaction time and excellent hands and back hook. Poor cardiopulmonary function, strength and jet lag in preparation stage. Action stage cardiopulmonary function and strength quality is poor, reaction time and flexibility is good. The female students have poor strength and flexibility in the expectation stage. In expected stage, the grip strength is qualified, the back hook is excellent, the reaction time is moderate and the relative VO₂ max is moderate. Action stage strength is poor, reaction time is medium, flexibility is excellent characteristic.Association with rule data mining can effectively discover the physical fitness characteristics of college students in different stages of physical exercise behavior and provide decision support for the promotion of physical fitness health of college students.