摘要
对田径短跑成绩的变化趋势进行分析,在提高田径运动成绩方面具有重要意义。由于田径短跑成绩容易受到周围环境,运动员体质等多方面的因素影响,使得成绩变化特征容易发生动态变化。传统的预测方法主要通过以往的田径短跑成绩特征对成绩变化趋势进行预测,忽略了周围环境及运动员体质不同带来的干扰,导致预测不准确,误差大的问题。提出基于改进支持向量机的奥运会田径短跑成绩变化趋势的动态分析方法。上述方法先采用统计学的原理对田径短跑成绩变化时间序列进行预测,并对相邻时间内奥运会成绩变化时间的相空间重构,将支持向量机和区间相空间原理相融合,给出成绩变化趋势回归方程,组建了奥运会田径短跑成绩变化趋势的动态分析模型,完成了对奥运会田径短跑成绩变化趋势的动态分析。仿真证明,所提算法为田径运动的发展提供参考。
In the paper,we proposed a dynamic analysis method based on the improved support vector machine in the Olympic track and field sprint performance change trend. In the above method,we first used the principle of statistics to predict the time series of track sprint performance. We reconstructed the phase space of the change time of Olympic performance in adjacent time. Support vector machine（ SVM） was combined with interval phase space theory to give the results change trend of regression equation. We established the dynamic analysis model of the changing trend of the track and field sprint performance in the Olympic Games,and completed the dynamic analysis of the changing trend of the track and field sprint performance of the Olympic Games. The simulation results show that the proposed algorithm provides reference for the development of track and field events.
出处
《计算机仿真》
CSCD
北大核心
2016年第10期417-420,共4页
Computer Simulation
关键词
奥运会
变化趋势
动态分析
Olympic Games
Change trend
Dynamic analysis
