数据挖掘技术在少年健康体育行为应用中的研究

发布时间：2018-06-20 10:00

本文选题：数据挖掘 + 少年健康体育行为　；参考：《现代电子技术》2017年09期

【摘要】：采用大数据分析方法进行少年健康体育行为统计分析,指导少年体育训练管理,提出基于数据挖掘技术的少年健康体育行为建模分析方法。首先采用模糊决策方法构建体育行为特征的实体模型,结合支持向量机进行体育行为大数据信息挖掘,构建数据挖掘的统计决策目标函数;然后采用粒子群方法进行挖掘目标函数的参数寻优,实现对少年健康体育行为大数据准确挖掘和特征分析。仿真结果表明,采用该方法进行少年健康体育行为应用分析,使体育关联数据挖掘准确度较高,统计分析的可靠性较好。
[Abstract]:The big data analysis method was used to analyze adolescent healthy sports behavior, to guide the management of juvenile sports training, and to put forward the modeling and analysis method of adolescent health sports behavior based on data mining technology. Firstly, the fuzzy decision method is used to construct the entity model of sports behavior characteristics, and the support vector machine (SVM) is used to mine sports behavior big data information, and the statistical decision objective function of data mining is constructed. Then the particle swarm optimization method is used to mine the parameters of the objective function to realize the accurate mining and feature analysis of the adolescent health sports behavior big data. The simulation results show that the application of this method to the analysis of adolescent health sports behavior makes the sports association data mining more accurate and the reliability of statistical analysis is better.
【作者单位】：许昌学院体育学院;
【分类号】：G804.49;TP311.13

【相似文献】