Author(s)

Bao Wei

Corresponding Author

Bao Wei

Abstract

To improve reasonability and accuracy of higher vocational teaching quality evaluation, higher vocational teaching quality evaluation system based on optimized deep neural networks of intelligent water drop algorithm (IWD) is put forward. Firstly, make use of on-line student evaluation system widely adopted by certain vocational technical college to perform evaluation index design, and aimed at nonlinearity existing among these indexes, make use of deep neural networks to perform higher vocational teaching quality evaluation system construction. Then utilize second order parameter optimization form to perform Hessian matrix solution, and realize simplification of training process of deep network learning. Finally, verify effectiveness of algorithm mentioned through experiment simulation.

Keywords

Higher Vocational Teaching Quality, Deep Neural Networks, Nonlinearity, Second Order Parameter, Hessian Matrix