Prediction of College Students’ Employment Rate Based on Gray System

Abstract

College students’ employment is affected by many factors such as economy and policy, which makes the prediction error of college students’ employment rate large. In order to solve this problem, a prediction method of college students’ employment rate based on the gray system is designed. Firstly, it analyzes the current research status of college students’ employment rate prediction, finds out the causes of errors, then collects the historical data of college students’ employment rate, fits the change characteristics of college students’ employment rate through the gray system, and establishes the prediction model of college students’ employment rate. Finally, the simulation test is realized by using the employment rate data of college students. The results show that the gray system can reflect the change characteristics of college students’ employment rate and obtain high-precision college students’ employment rate prediction results. The prediction error is less than that of other college students’ employment rate prediction methods. We achieved an average accuracy of 95.22% as compared to 92.3% and 87.7% of other proposed systems. The prediction results can provide some reference information for the university employment management department.