基于数据挖掘的运动员神经类型特征评估系统构建

Construction of athlete’s neural type feature evaluation system based on data mining

针对当前运动员训练信息化的需求,结合当前的数据挖掘算法,提出一种改进关联规则算法的运动员神经类型特征评估系统。对此,文章首先对评估系统设计的目标进行分析,并结合该目标,从整体架构、功能模块等方面进行了设计。在整体架构方面,采用C/S模式对系统架构进行搭建,以提高系统运行的速度,在功能模块方面,按照测试的流程,分为测试基本信息录入、测试评估模型和测试结果查询。同时在该系统设计中,重点就Apriori算法进行了研究,并且为了提高其对事务数据库扫描的效率,通过连接和剪枝的方式对其进行改进。最后通过某体育中心数据库数据对上述方案进行验证,并给出其实现的部分流程和结果。而通过研究,为当前运动训练的信息化提供了借鉴。

In view of the needs of the current athletes training information,and combined with the current data mining algorithm,an athlete neural type feature evaluation system is proposed to improve the association rules algorithm.In this regard,the paper first analyzes the design objectives of the evaluation system,and combines with the goal,and designs from the overall framework,function modules and so on.In the overall architecture,the C/S model is used to build the system architecture to improve the speed of the system operation.In the function module,according to the test process,it is divided into the test basic information entry,the test evaluation model and the test result query.At the same time,in the design of the system,the emphasis is on the research of Apriori algorithm,and in order to improve the efficiency of the transaction database scanning,it is improved by the way of connection and pruning.Finally,the above scheme is verified through the database data of a sports center,and some of the process and results of its implementation are given.Through research,it provides reference for current sports training informatization.