Fuzzy Neural Network Model for Comprehensive Quality Evaluation on College Students

Respective advantages of the fuzzy analysis and neural network with respect to evaluation are adopted herein to establish the fuzzy neural network model for comprehensive quality evaluation on college students. In order to speed up convergence of the network, the clustering analysis method was adopted in the process of training to cluster values of all indexes input. Number of the hidden layer nodes was chosen using similarity measure method. These measures have speeded up convergence of the network and optimized structure of the network. Examples have proved that this evaluation model can finish the evaluation work well.