体操运动员平衡木直体后空翻动作数据抗干扰挖掘

针对当前数据挖掘方法挖掘精度低、抗干扰能力差,挖掘效率低等问题,提出一种新的体操运动员平衡木直体后空翻动作数据抗干扰挖掘方法。给出体操运动员平衡木直体后空翻动作完成过程,利用体操运动员平衡木动作数据的预测值和实际值间的误差去除干扰数据。依据关联系数矩阵与差异性系数矩阵求出体操运动员平衡木直体后空翻动作数据集之间的关联映射,结合关联映射确定数据集间的关联规则,计算出同一空间下平衡木直体后空翻动作数据集之间的关联因子,获取两个数据集的挖掘公式,从而实现数据的抗干扰挖掘。实验结果表明,所提方法具有很高的挖掘精度和挖掘效率。

Gymnast balance beam stretched backward somersault movements anti-interference data mining

In view of the current data mining method mining low accuracy, poor anti-interference ability, low mining efficiency problem, put forward a new gymnast balance beam stretched backward somersault movements anti-interference data mining methods.Gymnasts are given the balance beam stretched back flip action to complete the process, using the gymnasts balance beam movement data error between the predicted and actual values remove interference data.According to the correlation coefficient matrix and difference coefficient matrix and gymnast balance beam stretched back flip the link between the data sets mapping, association mapping combined association rules between the data sets is determined, calculate the balance beam under same space stretched backward somersault movements associated factors between data sets, obtaining mining formula of two data sets, so as to realize the anti-interference of data mining.The experimental results show that the proposed method has high precision and the mining efficiency.