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Modeling and simulation of teaching quality in colleges based on BP neural network and training function

机译:基于BP神经网络和训练功能的高校教学质量的建模与仿真

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摘要

In order to realize the intelligent evaluation of effective teaching quality and make up for the lack of research in this aspect, in the research, BP neural network is used as the basis for model construction analysis. Political education in colleges and universities is an important course, and its teaching quality evaluation is particularly important. Through comparative analysis, LMBP is selected as the learning algorithm, and the neural network evaluation model mechanism of college classroom teaching quality evaluation system is determined through theory and practical methods, and the simulation model is simulated by MATLAB as a simulation tool. At the same time, this paper uses the experimental method to carry out simulation training experiments in the MATLAB neural network toolbox, select the training algorithm for comparative analysis, and display the results in the form of statistical graphs. In addition, this paper sets the convergence speed and error curve as evaluation indicators, determines the appropriate training algorithm, and verifies the validity of the model. The research indicates that the BP teaching quality evaluation model based on BP neural network is a reasonable and feasible evaluation model and can provide theoretical reference for subsequent related research.
机译:为了实现有效教学质量的智能评估,弥补在这方面的缺乏研究中,在研究中,BP神经网络被用作模型施工分析的基础。高校政治教育是一个重要的课程,其教学质量评估尤为重要。通过对比分析,选择LMBP作为学习算法,通过理论和实用方法确定高校课堂教学质量评估系统的神经网络评估模型机制,MATLAB模拟模拟模型作为模拟工具。同时,本文采用实验方法在MATLAB神经网络工具箱中进行仿真训练实验,选择比较分析的培训算法,并以统计图表的形式显示结果。此外,本文将收敛速度和错误曲线设置为评估指标,确定适当的培训算法,并验证模型的有效性。该研究表明,基于BP神经网络的BP教学质量评估模型是一个合理和可行的评估模型,可以为随后的相关研究提供理论参考。

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