基于GA优化RBF神经网络的英语教学质量评价  

Evaluation of English Teaching Quality Based on GA Optimized RBF Neural Network

作　　者：张居设[1] ZHANG Ju-She(Guangxi Vocational College of Technology and Business,Nanning 530008,China)

机构地区：[1]广西工商职业技术学院,南宁530008

出　　处：《计算机系统应用》2020年第3期167-172,共6页Computer Systems & Applications

摘　　要：针对目前英语教学质量评价准确性不高的问题,提出了一种基于遗传算法(GA)优化RBF神经网络的教学质量评价方法.首先利用主成分分析对教学质量评价指标进行选择,然后设计了RBF神经网络教学评价模型,并采用GA对RBF神经网络的初始权值进行优化.实验结果表明,该方法能够有效评价英语教学质量,且准确性和实时性较高.Aiming at the inaccuracy of English teaching quality evaluation,a teaching quality evaluation method based on Genetic Algorithm(GA)to optimize RBF neural network is proposed.Firstly,the principal component analysis is used to select the evaluation index of teaching quality,then the RBF neural network teaching evaluation model is designed,and the initial weight of RBF neural network is optimized by GA.The experimental results show that the method can effectively evaluate the quality of English teaching,and has high accuracy and real-time.

关 键 词：英语教学 质量评价 RBF神经网络 遗传算法 主成分分析 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] H319.3[自动化与计算机技术—控制科学与工程]