Research on the application of RBF neural network in the evaluation of college English teaching quality

Xin SHEN
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Abstract

Because of the diversity of teaching and students and the supervisory factors of the educational affairs department, it is difficult to be objective and fair in teaching quality evaluation. In order to solve the problems existing in the traditional teaching quality evaluation in colleges and universities and improve the accuracy of college teaching quality evaluation, this paper applies the RBF (Radial Basis Function) neural network to the evaluation of college English teaching quality. This paper builds a RBF neural network model for college English teaching quality evaluation, and verifies the accuracy of the RBF neural network through experiment. The results show that the RBF neural network established in this paper can evaluate the college English teaching quality well.
RBF神经网络在大学英语教学质量评价中的应用研究
由于教师和学生的多样性以及教务部门的监督因素,教学质量评价难以做到客观公正。为了解决传统高校教学质量评价中存在的问题,提高高校教学质量评价的准确性,本文将RBF (Radial Basis Function)神经网络应用到大学英语教学质量评价中。本文建立了用于大学英语教学质量评价的RBF神经网络模型,并通过实验验证了RBF神经网络的准确性。结果表明,本文所建立的RBF神经网络能够较好地评价大学英语教学质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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