摘要
针对体育运动员训练科学化的需求,文中结合数据挖掘技术,研究了一种改进的体育训练模式决策支持评估系统。对此,文中分析了关联规则算法的特点,详述了其数据的预处理、数据挖掘、模式评估的功能。结合对决策支持系统的软件设计,分析了系统运行的特点。同时,文中重点讲解了关联规则对体育评价决策支持系统中相关的数据融合处理,提出了改进Apriori算法输出模式,提高了系统评估的效果。通过对传统的Apriori算法、DC-Apriori算法和改进Apriori算法进行仿真对比可知,文中提到的改进Apriori算法能够有效地实现体育训练模式的决策支持。
In response to the demand for scientific training of sports athletes,this paper combines data mining technology to study an improved sports training model decision support evaluation system.In this regard,this paper first analyzes the characteristics of the association rule algorithm,and details the functions of data preprocessing,data mining,and pattern evaluation.Combined with the software design of the decision support system,the characteristics of system operation are analyzed.At the same time,this article focuses on explaining the association rules to the relevant data fusion processing in the sports evaluation decision support system,and proposes to improve the output mode of the Apriori algorithm to improve the effectiveness of the system evaluation.Finally,through the simulation comparison of traditional Apriori algorithm,DC-Apriori algorithm and improved Apriori algorithm,we can see that the improved Apriori algorithm mentioned in this article can effectively realize the decision support of sports training mode.
作者
王华满
WANG Huaman(Shaanxi Police Collge,Xi’an 710021,China)
出处
《电子设计工程》
2021年第5期114-117,123,共5页
Electronic Design Engineering
基金
陕西省教育厅课题(2019094)。
关键词
数据挖掘技术
关联规则
体育训练评价
数据融合处理
data mining technology
association rules
evaluation of sports training
data fusion processing
