摘要
提出了一种随机型时间序列预测的新方法，特别适用于趋势随机型数据序列的预测问题，与现有预测方法相比，具有计算简单。
This paper presents a new mathematical model for forecasting stochastic time series, which combines the linear regression or nonlinear regression with Markov probability forecasting.It has the merits of both simplicity of application and high forecasting precision. In particular, the forecast values of the model are more precise than those of other models such as index smoothing method and grey dynamic model,for data sequences with heavy random fluctuation. The case study of the cotton production in cixi city, Zhejiang province show that the forecasting precision of the model is satisfactory.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
1997年第1期36-43,共8页
Systems Engineering-Theory & Practice
关键词
预测
时间序列分析
状态
数学模型
forecast
time series anslysis
state analysis
mathematical model
