An improved GRA algorithm for teaching quality evaluation of college physical education based on the probabilistic simplified neutrosophic sets

被引:0
|
作者
Gao, Kelian [1 ]
Yu, Fangqing [1 ]
机构
[1] Yulin Univ, Sch Phys Educ, Yulin, Shaanxi, Peoples R China
关键词
Multiple attributes decision making (MADM); probabilistic simplified neutrosophic sets (PSNSs); GRA method; Teaching quality evaluation; AGGREGATION OPERATORS; COMPREHENSIVE EVALUATION; EVALUATION SYSTEM; SIMILARITY;
D O I
10.3233/JIFS-231728
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the emergence of various new teaching concepts and teaching models in colleges and universities, the original evaluation system can no longer fully meet the requirements of the current development of physical education curriculum teaching in colleges and universities. Thus, reducing the judgment and guidance of evaluation on physical education curriculum teaching shall result in the development of physical education curriculum teaching quality evaluation lagging behind the development of teaching and being in a passive position. Therefore, it is particularly important to establish a new evaluation standard system for the teaching quality of physical education courses. The teaching quality evaluation of college physical education (PE) is viewed as multiple attribute decision-making (MADM). In this paper, an enhanced probabilistic simplified neutrosophic grey relational analysis (PSN-GRA) method is designed for MADM. Then, in the environment of probabilistic simplified neutrophil set (PSNSs), the PSN-GRA method and CRITIC method are combined to rank the alternative schemes, and a numerical example of college physical education teaching quality evaluation proves the practicability of the newmethod and compares it with other methods. The results show that this method is simple, effective and simple in calculation.
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页码:5199 / 5210
页数:12
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