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運動員跑步強度訓(xùn)練關(guān)節(jié)損傷優(yōu)化預(yù)測仿真

發(fā)布時間:2018-06-12 18:12

  本文選題:跑步強度訓(xùn)練 + 關(guān)節(jié); 參考:《計算機仿真》2017年11期


【摘要】:對運動員跑步強度訓(xùn)練下關(guān)節(jié)損傷的優(yōu)化預(yù)測,能夠有效提升運動員競技體育水平。對關(guān)節(jié)損傷的預(yù)測,需要選取對損傷有顯著影響的因素作為自變量,計算損傷統(tǒng)計量的顯著性篩選變量,完成跑步訓(xùn)練下運動員關(guān)節(jié)損傷的預(yù)測。傳統(tǒng)方法分析關(guān)節(jié)損傷數(shù)據(jù)源矩陣中元素的統(tǒng)計特性,利用線性特征值統(tǒng)計量作為相關(guān)性指標(biāo),但忽略了計算出損傷統(tǒng)計量的篩選變量,導(dǎo)致預(yù)測精度偏低。提出基于二元Logistic逐步回歸分析的跑步強度訓(xùn)練下關(guān)節(jié)損傷分析方法。建立關(guān)節(jié)損傷影響因素分析模型,加強訓(xùn)練負(fù)荷強度對損傷因素的影響機理和因素間的作用關(guān)系,進行運動員關(guān)節(jié)損傷特征分析,將運動員超負(fù)荷訓(xùn)練程度作為因變量,選取對損傷有顯著影響的因素作為自變量,計算損傷統(tǒng)計量的顯著性篩選變量,對關(guān)節(jié)損傷進行預(yù)測。實驗結(jié)果表明,所提方法能夠有效提升競技比賽成績提供了科學(xué)依據(jù)和指導(dǎo)。
[Abstract]:The optimal prediction of joint injury under intensity training can effectively improve the athletic level of athletes. For the prediction of joint injury, it is necessary to select the factors that have significant influence on the injury as independent variables, calculate the significant screening variables of injury statistics, and complete the prediction of joint injury of athletes under running training. The traditional method is used to analyze the statistical characteristics of the elements in the joint injury data source matrix. The linear eigenvalue statistics are used as the correlation index, but the filtering variables of the damage statistics are neglected, which leads to the low prediction accuracy. A method of joint damage analysis under running intensity training based on binary Logistic stepwise regression analysis was proposed. This paper establishes the analysis model of the influencing factors of joint injury, strengthens the influence mechanism of the training load intensity on the injury factors and the action relationship among the factors, analyzes the characteristics of the athletes joint injury, and takes the training degree of the athletes' overload as the dependent variable. The factors which have significant influence on the injury were selected as independent variables, and the significant screening variables were calculated to predict the joint injury. The experimental results show that the proposed method can effectively improve the performance of competitive competition to provide scientific basis and guidance.
【作者單位】: 平頂山學(xué)院體育學(xué)院;
【分類號】:G822;O212
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本文編號:2010612

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