基于BP神经网络的高等中医院校本科生就业地域预测模型研究

A Research of the Prediction Model of Employment Region of Undergraduate Students from TCM Colleges and Universities Based on BP Neural Network

本文旨在研究不同高等中医院校本科生招生与就业的地域关系。依据各省(市)人均GDP数据表征招生生源及毕业生就业省(市)经济发达程度、各省(市)招生分数排名表征招生生源质量、地理条件、生活习惯及宗教信仰综合表征毕业生就业地域认可度,得出影响因子矩阵并构建训练良好的BP神经网络模型。本文试图对招生计划进行调整,通过已训练良好的BP神经网络模型进行仿真计算,预测不同地域就业比例变动。

The paper studied the regional relation between student enrollment and employment of undergraduate students from different TCM colleges and universities. The economic development degrees of the provinces providing student resource and the provinces providing employments were reflected by the GDP per capita of respective provinces （municipalities）, the student resource quality was reflected by the ranking of test scores for enrollment of respective provinces （municipalities） and the recognition degree of graduates toward the employment territory was comprehensively reflected by geographical conditions, living habits and religious beliefs. Thus, an influencing factor matrix was produced and then a well-trained BP neural network model was obtained. At last, the paper adjusted the undergraduate enrollment plan and predicted the change of employment proportion of graduates through the simulating calculation based on the well-trained BP neural network model.