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Matlab and linear fitting-based university students physical health evaluation model study

机译:基于Matlab和线性拟合的大学生身体健康评估模型研究

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In order to make reasonable evaluation on university students physical health, the paper firstly gets each factor and weight relationship by linear fitting method according to collected data, obtains six relations, and use MATLAB to make the image of every relation, observes images and then we get that weight and each factor relationship are inclined to be positive distributed, combines with relations,it gets that when weight is 90 to 100KG, height and lung capacity test results are the best, when weight is 70 to 90KG, step, long jump and grip test results are the best, while for schoolgirls test item sit and reach, when weight is 50 to 60KG, sit and reach results are the best. Use grey relational degree method to solve correlation coefficient, calculate weights, and then combine percentile method with mean and standard deviation, it solves a relative standard four items test data, finally use students actual measurement data to divide every item physical health test result and respectively multiply by respective weight, it gets respective scores, and then rank scores, assume that x% is qualified, then through students’ results ranking, use x% to distinguish result, the ones that are higher the result is supposed to be qualified, otherwise is failed, so that it can quantize physical health indicators.
机译:为了对大学生的身体健康做出合理的评价,本文首先根据采集到的数据通过线性拟合的方法得到各因子和权重的关系,得到六个关系,并用MATLAB制作各关系的图像,观察图像,然后得出体重与各个因素之间的关系倾向于正分布,并结合关系得出,体重在90至100KG时,身高和肺活量测试结果是最佳的;体重在70至90KG时,踏步,跳远和握力测试结果是最好的,而对于女学生而言,坐着并达到测试结果,当体重为50至60KG时,坐着并达到结果是最好的。用灰色关联度法求解相关系数,计算权重,再将百分位数法与均值和标准差相结合,求解出相对标准的四项测试数据,最后利用学生的实际测量数据分别划分各项健康测试结果和乘以各自的权重,得到各自的分数,然后对分数进行排名,假设x%是合格的,然后通过学生的成绩排名,使用x%来区分结果,认为结果较高的那个才是合格的;否则失败,因此它可以量化身体健康指标。

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