基于概率神经网络的高校毕业生学位评审预测

Evaluation and Forecasting of College Graduate Degree Based on Probability Neural Network

客观地、高效地、准确地对高校毕业生获得学位进行评审,是高校面临的一个重要问题.本文首先提取影响毕业生学位的评审五大指标:学习成绩、实习成绩、论文成绩、英语四级、计算机等级,然后建立了概率神经网络的高校毕业生学位评审模型.Matlab仿真实验表明,该方法评审学位简单快速且准确率较高,具有良好应用前景,也为今后高校学位评审提供一个新视角.

It is important for a college to establish an objective,efficient and accurate college graduate degree evaluation forecasting system.Five characters of College graduate degree evaluation,study result,practice result,paper results,English four class and computer level,are distilled for the input data.A PNN model was obtained for College graduate degree evaluation.The highly accurate result simulated by Matlab shows that the PNN is simply-built and runs fast,and is an effective method of College graduate degree evaluation.