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Development Assessment of Higher Education System Based on TOPSIS‐Entropy, Hopfield Neural Network, and Cobweb Model
Author(s) -
Xian-Bei Liu,
Yujing Zhang,
Wen-Kai Cui,
Liting Wang,
Jiaming Zhu
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/5520030
Subject(s) - artificial neural network , topsis , hopfield network , computer science , entropy (arrow of time) , artificial intelligence , machine learning , mathematics , operations research , thermodynamics , physics
This paper first extracted 11 indicators from four aspects of infrastructure, educational equity, teaching quality, and scientific research level and established a multidimensional higher education evaluation system. After that, according to TOPSIS and the entropy method, a comprehensive score of the development of higher education was obtained, and a comprehensive index of higher education was proposed. According to the level of the score, we divide the development status into 5 categories, and use discrete Hopfield neural network for verification. In addition, we applied the model to many countries and chose Vietnam to conduct an in-depth analysis of the model, including reforming policies and evaluating policy effects based on cobweb model. Finally, we found that the application of the model is very universal, but in reality the reform is very difficult.

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