The application of multiple linear regressions in swimming fatigue degree assessment

Qicheng Wei; Xiaona Zhu

首页> 外文期刊>BioTechnology: An Indian Journal >The application of multiple linear regressions in swimming fatigue degree assessment

【24h】

The application of multiple linear regressions in swimming fatigue degree assessment

机译：多元线性回归在游泳疲劳程度评估中的应用

获取原文

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Fatigue degree assessment has a significant role in guiding for training strategies. This paper collected heart rate data during the eight weeks of training and subjective questionnaire data of the fatigue degree of 31 swimmers.Among themheart rate data is composed of five data: the heart rate value when getting up early in the morning, the heart rate value during the training preparation, the heart rate value when intensity of training is the largest, the heart rate value when finishing the training and the heart rate value when finishing the recovering. Subjective questionnaire data of the fatigue degree is composed of three data: the negative evaluation value, the physical strength overdraft value and the reduced value of confidence degree. Through heart rate data of the entire process, explore its relationship with the three items???? data of the fatigue degree, and establish a multiple linear regression model. After data test, model has good fitting degree and significance. It is reasonable to use the model to evaluate the fatigue degree of athletes.

机译：疲劳程度评估在指导培训策略中起着重要作用。本文收集了运动训练八周期间的心率数据和31名游泳者疲劳程度的主观问卷数据，其中心率数据由五个数据组成：清晨起床时的心率值，心率值在训练准备过程中，训练强度最大时的心率值，训练结束时的心率值和恢复后的心率值。疲劳程度的主观问卷数据由三个数据组成：负评估值，体力透支值和置信度降低值。通过整个过程的心率数据，探索其与三个项目的关系？数据的疲劳程度，并建立多元线性回归模型。经过数据测试，模型具有良好的拟合度和意义。使用该模型评估运动员的疲劳程度是合理的。

著录项

来源
《BioTechnology: An Indian Journal》 |2013年第1期|共4页
作者
Qicheng Wei; Xiaona Zhu;
展开▼
作者单位

展开▼
收录信息
原文格式 PDF
正文语种
中图分类生物工程学（生物技术）;
关键词
Trainingegression modelThe degree of fatigueFunctional recovery;

机译：训练回归模型疲劳程度功能恢复;

相似文献

外文文献
中文文献
专利

1. An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids [J] . Zapadka Mariusz, Kaczmarek Mateusz, Kupcewicz Bogumila, Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis . 2019,第期

机译：QSRR方法及多元线性回归方法对黄酮类化合物亲脂性评估的应用
2. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry [J] . Broadhurst D, Goodacre R, Jones A, Analytica chimica acta . 1997,第1a3期

机译：遗传算法作为多元线性回归和偏最小二乘回归中变量选择的一种方法，并应用于热解质谱
3. Application of random forest regression and comparison of its performance to multiple linear regression in modeling groundwater nitrate concentration at the African continent scale [J] . Ouedraogo Issoufou, Defourny Pierre, Vanclooster Marnik Hydrogeology journal . 2019,第3期

机译：随机森林回归及其性能比较在非洲大陆规模下地下水硝酸盐浓度模拟中的多元线性回归
4. Application of Multiple Nonlinear Regression Based on SPSS in The Risk Assessment of Debris Flow [C] . Qiuling Lang, Guangjie Li, Jingli Huang International Conference on Advanced Engineering Materials and Technology . 2013

机译：多元非线性回归在碎片流量风险评估中的应用
5. A COMPARISON OF UNBIASED, BIASED, AND WEIGHTED MULTIPLE LINEAR REGRESSION APPROACHES TO SUPPORT EDUCATIONAL POLICY IN THE IDENTIFICATION OF OUTLIER SCHOOLS (RIDGE REGRESSION, PREDICTION, RESIDUAL, EXPLANATION, NEEDS, ASSESSMENT) [D] . BIGELOW, ROBERT ASHLEY. 1984

机译：比较，偏重和加权的多元线性回归方法来支持对局外学校的教育政策的识别（岭回归，预测，残差，解释，需求，评估）
6. Application of Multiple Linear Regression and Artificial Neural Networks for the Prediction of the Packing and Capsule Filling Performance of Coated and Plain Pellets Differing in Density and Size [O] . Panagiotis Barmpalexis, Ioannis Partheniadis, Konstantina-Sepfora Mitra, 2020

机译：多元线性回归和人工神经网络在密度和尺寸不同的包衣和普通颗粒的包装和胶囊填充性能预测中的应用
7. Table 1: Model Regression Coefficients Estimated by Multiple Linear Regressions for the degree of hydrolysis (DH), DPPH radical-scavenging activity (DPPH) and ABTS radical-scavenging activity (ABTS) of MMPHs.a [O] . -1

机译：表1：模型回归系数由多元线性回归估计，用于水解程度（DH），DPPH激进的活性（DPPH）和MMPHS的自由基清除活动（ABTS）
8. MULTIPLE REGRESSION TECHNIQUE FOR Pth DEGREE POLYNOMIALS WITH AND WITHOUT LINEAR CROSS PRODUCTS [R] . John William Davis 1973

机译：具有和不具有线性交叉产物的pth次多项式的多重回归技术

The application of multiple linear regressions in swimming fatigue degree assessment

摘要

著录项

相似文献

相关主题

期刊订阅