基于独立模型的非线性时间序列多步超前预测

Multistep-Ahead Independent Prediction of Nonlinear Time Series Based on Independent Model

提出一种非线性时间序列的多步超前独立预测方法.对比逐步递归方法和独立预测方法,分析了积累误差对多步超前预测性能的影响.采用递归神经网络(RNN)实现了独立预测方法,建立了城市轨道交通能耗预测模型.通过MATLAB训练和测试该模型,比较了两种方法下的多步超前预测输出.结果表明,独立预测方法的误差优于逐步递归方法.最后指出了独立预测方法的优缺点及适用范围.

A multistep-ahead independent prediction approach of nonlinear time series was proposed. The step-by-step recurrent approach and the independent approach were compared, and the influence of accu- mulative error on the performance of multistep-ahead prediction was analyzed. The recurrent neural network （RNN） was used to realize the independent prediction approach, and the predictive model of urban rail transit is built, trained and tested by MATLAB. The predictive results showed that the error of inde- pendent prediction was smaller than that of step-by-step recurrent approach. The advantages and disadvantages of each approach were analyzed.