基于粗糙集和人工神经网络的普通学院英语四级通过率预测模型研究

2010 International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2010-11-18 DOI:10.1109/ICAIE.2010.5641104

Ying Zhang

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引用次数: 0

摘要

本文通过对部分班级进行调查，并基于粗糙集对相关因素进行约简，找出影响学生英语四级通过率的核心因素和最小约简，分析了影响学生英语四级通过率的主要因素，并用人工神经网络建立了低通过率的预测模型。在这种情况下，一般学院将原有的后控制转变为前控制，最大限度地避免低通过率。

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Study on forecasting model of CET4 passing-rate in general academy with rough set & ANN

This paper analyses main factors influencing CET4 passing-rate after investigating some classes and reducing related factors based on rough set to find out the core factor and minimum reduction, and then sets up forecasting model of low passing rate with ANN. In virtue of this situation, to switch original post-controlling into pre-controlling in general academy is expected to avoid low passing-rate in maximum.

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2010 International Conference on Artificial Intelligence and Education (ICAIE)

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