摘要
在GM(1,1)预测模型基础上,构建2个不同的预测模型——GM(1,1)幂模型和对原始数据进行缓冲算子处理的GM(1,1)模型,采用Matlab建模,并将模型应用到铁路客流量预测,分析对中小样本振荡序列的预测效果。实例证明,GM(1,1)幂模型和对原始数据进行缓冲算子处理的GM(1,1)模型的应用范围和预测精度都优于灰色GM(1,1)模型,是非线性铁路客流量预测的一种有效方法,有助于制定铁路运输计划。
Based on the GM （ 1,1 ） prediction model, two different prediction models, the GM （ 1, 1 ） power model and the GM （ 1,1 ） model for buffer operator processing of the original data, are constructed in the paper. The Matalb modeling is applied to the prediction of the railway passenger flow and to the analysis of the prediction effect of oscillatory sequence of＇ small and medium-sized samples. The example proves that the GM （ 1, 1 ） power model and the GM （ 1,1 ） model for buffer operator processing of the original data are better than the GM （ 1, 1 ） model in the application range and prediction precision, which is an effective calculation method for the nonlinear prediction of railway passenger flow and contributes to the decision-making of railway transportation.
出处
《山东交通学院学报》
CAS
2017年第1期29-33,共5页
Journal of Shandong Jiaotong University
关键词
灰色模型
非线性数列
铁路客流
预测
序列算子
grey model
nonlinear sequence
railway passenger flow
prediction
sequence operator
