经典灰色预测模型与Markov模型在高校招生人数预测中的比较研究——以河南省为例

Comparative Study of Classical Grey Prediction Model and Markov Model in College Enrollment Forecast--Through Taking Henan Province as an Example

高校招生人数是一个非平稳的时间序列,为比较经典灰色预测模型与Markov模型在预测高校招生人数中的优势,验证序列模型的可行性和精确度,以河南省高校招生人数为例,分别利用两个模型对其进行预测。通过预测发现,经典灰色预测模型可以对数据较少的序列进行预测,与其相比,Markov模型在非平稳的波动预测方面具有更高的精确度,可为相关教育部门和高校的招生工作提供一定的参考和指导。

The number of college students is a non-stationary time series.In order to compare the advantages of classical grey prediction model and Markov model in predicting college enrollment,and verify the feasibility and accuracy of sequence model,the study takes college enrollment in Henan Province as an example,and predicts the enrollment with two models.The prediction shows that classical grey prediction model can predict the sequence with less data,and Markov model has more accuracy in non-stationary wave prediction,which can provide certain reference for related education section and college enrollment.