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Received:July 29, 2019 Revised:September 03, 2019
Received:July 29, 2019 Revised:September 03, 2019
中文摘要: 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.
Abstract: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.
keywords: English teaching quality evaluation RBF neural network Genetic Algorithms (GA) principal component analysis
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| Author Name | Affiliation | |
| ZHANG Ju-She | Guangxi Vocational College of Technology and Business, Nanning 530008, China | zhangjs7507@sina.com |
| Author Name | Affiliation | |
| ZHANG Ju-She | Guangxi Vocational College of Technology and Business, Nanning 530008, China | zhangjs7507@sina.com |
引用文本：
张居设.基于 GA 优化 RBF 神经网络的英语教学质量评价.计算机系统应用,2020,29(3):167-172
ZHANG Ju-She.Evaluation of English Teaching Quality Based on GA Optimized RBF Neural Network.COMPUTER SYSTEMS APPLICATIONS,2020,29(3):167-172
张居设.基于 GA 优化 RBF 神经网络的英语教学质量评价.计算机系统应用,2020,29(3):167-172
ZHANG Ju-She.Evaluation of English Teaching Quality Based on GA Optimized RBF Neural Network.COMPUTER SYSTEMS APPLICATIONS,2020,29(3):167-172
