Evaluation of Higher Education System by TOPSIS Based on Entropy Weight Method
Authors
Feng He1, Qing Ye1, *, Sini Chen2
1Department of Computer Science, Yangtze University, Jingzhou, 434000, Hubei, China
2Department of Telecommunications, Yangtze University, Jingzhou, 434000, Hubei, China
*Corresponding author.
Email: yeqing@yangtzeu.edu.cn
Corresponding Author
Qing Ye
Available Online 23 December 2022.
- DOI
- 10.2991/978-94-6463-034-3_127How to use a DOI?
- Keywords
- Higher education system; Entropy method; TOPSIS; SA-BP neural network
- Abstract
The healthy and sustainable development of the higher education system is of great significance to the progress of a country. Based on public data, this paper uses topsis model based on entropy weight method, simulated annealing algorithm, bp neural network algorithm, fuzzy comprehensive evaluation, establishes a model set, and analyzes different problems. Besides, we also carried out a sensitivity analysis to increase each indicator byin countries other than the policy suggestion country, and then evaluated through our evaluation model. The results showed that our policy model has good stability.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Feng He AU - Qing Ye AU - Sini Chen PY - 2022 DA - 2022/12/23 TI - Evaluation of Higher Education System by TOPSIS Based on Entropy Weight Method BT - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022) PB - Atlantis Press SP - 1234 EP - 1241 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-034-3_127 DO - 10.2991/978-94-6463-034-3_127 ID - He2022 ER -