Research on Innovation Education Evaluation for Vocational College Based on Improved BP Neural Network
- DOI
- 10.2991/emehss-18.2018.26How to use a DOI?
- Keywords
- Education performance management, Innovation education performance evaluation, BP neural network, Fourier basis functions.
- Abstract
Along with the smooth advancement of a new round basic education reform, the profound changes have occurred in vocational college education ideology and teaching modes, which demands the reformation of innovation course education evaluation system to guarantee the acceleration of the reform. The paper presents a new model for evaluating innovation education for vocational college performance based on improved BP neural network. First an evaluation indicator system of innovation education performance is designed through the aspects of vocational college regulation and teachers and students and education effects; Second considering that BP neural network algorithm has high evaluation accuracy but low convergence, the paper adopts Fourier basis functions to improve traditional BPNN algorithm to speed up model convergence and to simplify model structure; Finally the experimental results show that the new evaluation indicator system and improved BP neural network algorithm can be used practically in evaluating innovation education for different vocational colleges and guarantee the evaluation effectiveness and validity.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hui Zhang PY - 2018/03 DA - 2018/03 TI - Research on Innovation Education Evaluation for Vocational College Based on Improved BP Neural Network BT - Proceedings of the 2nd International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2018) PB - Atlantis Press SP - 130 EP - 134 SN - 2352-5398 UR - https://doi.org/10.2991/emehss-18.2018.26 DO - 10.2991/emehss-18.2018.26 ID - Zhang2018/03 ER -