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Teaching Evaluation Algorithm Based on Grey Relational Analysis

机译:基于灰色关系分析的教学评估算法

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摘要

Grey correlation analysis uses grey correlations to describe the strength, magnitude, and order of relationships among factors. The data sequence of the drmined data is used as a reference data string, and the data sequence matrix of each influence factor is used as a control data matrix to calculate the correlation between the data sequence and the reference of each factor in the control data matrix. The basic idea of quantitatively measuring the correlation between each factor and the object is to determine the similarity between the reference data sequence and the shape of multiple comparison data sequences and to determine whether the connection is strong. It reflects the degree of correlation between curves. In this paper, we examine the problem of evaluating the quality of undergraduate education by multiple indicators and establish a comprehensive evaluation model of the quality of undergraduate education in the 13 prefecture level cities by using the grey correlation analysis. The correlation coefficient of each index was obtained by the grey correlation analysis, the correlation number of each index was analyzed and ranked, and finally the improvement of the number of “advanced teachers” and the education of 13 prefectures were reduced as much as possible.
机译:灰色相关性分析使用灰色相关来描述因素之间的关系的强度,幅度和顺序。 DRMined数据的数据序列用作参考数据串,每个影响因子的数据序列矩阵用作控制数据矩阵,以计算数据序列与控制数据矩阵中的每个因子之间的相关的相关性。定量测量每个因子与对象之间的相关性的基本思想是确定参考数据序列与多个比较数据序列的形状之间的相似性,并确定连接是否强。它反映了曲线之间的相关程度。在本文中,我们通过使用灰色相关分析,研究了多个指标评估本科教育质量的问题,并建立了灰色相关分析的综合评价综合评价。通过灰色相关分析获得每个指标的相关系数,分析和排名各指数的相关数,最后改善了“高级教师”的数量和13个县的教育尽可能减少。

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