Fuzzy comprehensive quality evaluation on undergraduate students based on lobe component analysis

Respective advantages of the fuzzy analysis and lobe component analysis with respect to evaluation are adopted to establish the fuzzy lobe component analysis model for comprehensive quality evaluation on undergraduate 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. These measures have speeded up convergence of the network and optimized structure of the network. Especially, the method performs unsupervised learning while the input samples are being classified. Examples have proved that this evaluation model can finish the evaluation work well.