摘要
研究运动强度与身体疲惫关系问题,可以很好地避免过度运动而对身体造成的损害。由于身体疲惫又与运动强度大小等多因素有关,使得运动强度与身体疲惫之间存在高随机性关系。传统的建模方法针对上述关联性仅仅以对过去的数据统计的方式完成关系建模,没有考虑众多的约束条件,导致建模效果差、准确性低。提出采用支持向量机的运动强度与身体疲惫程度的关系建模方法,依据支持向量机原理,找到一个最优超平面,使得在给定精度条件下能够以无误差拟合,将当前寻优问题转换成最小化模型复杂度问题,引入松弛变量与惩罚系数,将优化问题转换成对偶问题,对最优回归函数进行求解,建立运动强度与身体疲惫程度的关系模型。仿真结果表明,所提方法能够有效提高运动强度与身体疲惫程度关系表达的准确性。
Study of the relationship between exercise intensity and physical exhaustion can be very good to avoid the damage to the body caused by the excessive exercise. Because physical exhaustion is related to many factors such as the size of exercise intensity, making that it has a high randomness relationship between exercise intensity and physical exhaustion. Traditional modeling method used for the above mentioned relevance can only use the past data statistics pattern to make relationship modeling, without considering many constraints, leading to poor modeling effect and low accuracy. A modeling method for the relationship between exercise intensity and the degree of physical exhaustion based on support vector machine （SVM） is proposed. According to the theory of support vector machine （ SVM）, an optimal hyperplane is found out, to make error free fitting under the condition of the given precision. The current optimal problem is transformed into the issue of minimization model complexity, and introducing the slack var- iable and punish coefficient, the optimization problem is transformed into the dual problem, to solve the optimal re- gression function, and establish the relationship model between exercise intensity and the degree of physical exhaus- tion. The simulation results show that the proposed method can effectively improve the expression accuracy of the relationship between exercise intensity and the degree of physical exhaustion.
出处
《计算机仿真》
CSCD
北大核心
2016年第1期400-403,共4页
Computer Simulation
关键词
运动强度
身体疲惫程度
关系建模
Exercise intensity
Degree of physical exhaustion
Relationship modeling
