Proceedings of the 2016 International Conference on Education, Management and Computer Science

The Empirical Analysis of Teaching Quality Guarantee System for Universities Based on the Fuzzy Comprehensive Evaluation and Fuzzy Neural Network Models

Authors
Chunfeng Liu, Peiluan Li, Baoan Li
Corresponding Author
Chunfeng Liu
Available Online May 2016.
DOI
https://doi.org/10.2991/icemc-16.2016.213How to use a DOI?
Keywords
University teaching quality; Guarantee system; Analytic hierarchy model; Fuzzy comprehensive evaluation model; Fuzzy neural network model
Abstract
In this paper, the modeling analysis about teaching quality guarantee system is discussed. In Henan University of Science and Technology, for example, first the corresponding questionnaire survey has been made, then using the method of analytic hierarchy structure and fuzzy comprehensive evaluation to establish the teaching quality guarantee system of the secondary fuzzy comprehensive evaluation model, finally the fuzzy neural network model of university teaching quality guarantee system is established.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Volume Title
Proceedings of the 2016 International Conference on Education, Management and Computer Science
Series
Advances in Intelligent Systems Research
Publication Date
May 2016
ISBN
978-94-6252-202-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/icemc-16.2016.213How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chunfeng Liu
AU  - Peiluan Li
AU  - Baoan Li
PY  - 2016/05
DA  - 2016/05
TI  - The Empirical Analysis of Teaching Quality Guarantee System for Universities Based on the Fuzzy Comprehensive Evaluation and Fuzzy Neural Network Models
BT  - Proceedings of the 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SP  - 1094
EP  - 1103
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.213
DO  - https://doi.org/10.2991/icemc-16.2016.213
ID  - Liu2016/05
ER  -