基于学习矢量量化(LVQ)神经网络的高校毕业生学位评审预测

摘要

It is an important issue how to set up an objective and efficient model for the prediction of college graduate degree evaluation. Based on the learning vector quantization neural network, the college graduate degree parameters such as learning performance,practice results,grades of thesis,CET4 and computer grades are considered. Then the actual data of a college are used as an example to verify the predictive capability of the method. The result indicates that the above model can be a great help to decision makers.%利用影响毕业生学位评审的五大指标:学习成绩、实习成绩、论文成绩、英语四级、计算机等级,提出基于学习矢量量化LVQ(Learning Vector Quantization,LVQ)神经网络的高校毕业生学位评审预测模型.以某高校某专业毕业生的实际数据为例,验证了此方法的预测能力.结果表明,基于LVQ神经网络的高校毕业生学位评审预测模型,能为评审学位的工作者提供有益的辅助参考.