摘要
为了有效准确地评价教学质量,提出了一种基于遗传算法(GA)和反向传播神经网络(BPNN)的混合智能算法,用于评价教学质量.首先建立教学质量评价指标体系,根据指标体系设计调查问卷,收集数据,并通过GA优化BPNN参数方法建立教学质量评价模型.通过MATLAB2013b进行仿真实验,依据预测精度评价模型的性能,并与仅由反向传播神经网络方法建立的模型进行比较.预测精度提高15.45%,表明基于GA-BPNN教学质量评价模型能够有效实现教学质量的评价.
In order to evaluate the teaching quality effectively and accurately,a hybrid intelligent algorithm based on genetic algorithm （GA） and back propagation neural network （t3PNN） is pro- posed. Firstly,the teaching quality evaluation index system is set up, the questionnaire is designed according to the index system, the data are collected, and the teaching quality evaluation model is es- tablished by GA optimizing BPNN parameter method. Through MATLAB2013b simulation experi- ments, the performance of the model is evaluated according to the prediction accuracy and compared with the model established by the method of BPNN. The prediction accuracy improves 15. 45%, which shows that the GA-BPNN teaching quality evaluation model can effectively evaluate the teaching quality.
作者
岳琪
温新
YUE Qi,WEN Xin(College of Information and Computer Engineering, The Northeast Forestry University, Harbin 150040, Chin)
出处
《内蒙古大学学报（自然科学版）》
CAS
北大核心
2018年第2期204-211,共8页
Journal of Inner Mongolia University：Natural Science Edition
基金
黑龙江省教育厅规划课题(GJC1316036)
关键词
遗传算法
BP神经网络
教学质量评价模型
指标体系
genetic algorithm
BP neural network
evaluation model of teaching quality
index system
