Teaching Evaluation Algorithm Based on Grey Relational Analysis
| Autor: | Xiaoying Zhang, Jing Yang, Xiuying Yang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Sequence
Multidisciplinary Article Subject General Computer Science Correlation coefficient 020209 energy String (computer science) Reference data (financial markets) QA75.5-76.95 02 engineering and technology Grey relational analysis Correlation Similarity (network science) Electronic computers. Computer science Multiple comparisons problem Statistics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Mathematics |
| Zdroj: | Complexity, Vol 2021 (2021) |
| ISSN: | 1099-0526 1076-2787 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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