基于组合神经网络的教师评价模型研究

本文提出的基于组合神经网络的教师评价模型,可以弥补以往基于神经网络的教师评价模型的不足,不但可以给出教师的综合得分或所属类别,还可以给出教师在每个方面的得分.所使用的组合神经网络,由多个结构相同的BP神经网络组成;用构建的组合神经网络和传统BP神经网络分别进行实验.仿真实验表明,该模型相对误差较小,可以满足评价需求.

A Study of Teachers Evaluation Model Based on Combination Neural Network

In this paper,teachers evaluation model based on the combination of neural network is presented.This model may make up for the past model based on neural networks inadequate.And this model not only gives the teacher's score or category,but also gives teacher's score in every aspect.Then several feedforward neural networks are assembled into an ensembled neural network.Each of these feedforward neural networks is same in structure and trained by using the BP learning algorithm.The combination neural network has been compared with the conventional BP neural network on their performance.The results of experiments indicate: the relative error is smaller,so the model is validated.