RBF神经网络在高职院校教师质量评价体系中的应用

Application of RBF Neural Network in the Evaluation System of Teachers' Quality in Higher Vocational Colleges

高职院校教学质量是其生存和发展的基础,而教师质量是高职院校办学质量保障体系中的重要组成部分。为了客观、多元化的评价教师质量,真实反映教师水平和能力,本文首先提出高职院校教师质量评价体系和指标,再通过RBF神经网络理论确立基于RBF神经网络的高职院校教师质量评价模型,并经样本数据进行仿真验证。通过仿真数据表明,该模型能够较全面、科学地评价教师质量。

The quality of teaching in higher vocational colleges is the basis of its survival and development,and the quality of teachers is an important part of the quality assurance system in Higher Vocational colleges.In order to objectively and diversified evaluation the quality of teachers,teachers reflect the level and ability of teachers in higher vocational colleges,this paper puts forward the quality evaluation system and index,and then through the RBF neural network theory to establish the vocational college teachers RBF neural network evaluation model based on quality,and is verified by the sample data.The simulation results show that the model can comprehensively and scientifically evaluate the quality of teachers.