Double Trends Time Series Forecasting Using a Combined ARIMA and GMDH Model

摘要：

The time series of monthly cigarette sales have double trends which include long-term upward trend and seasonal fluctuations trend. For this complex system forecasting, single linear or nonlinear forecasting model can’t deeply capture characteristics of the data so the results are imprecise. In this paper, a combined methodology that combines both ARIMA and GMDH models is proposed to take advantage of the unique strength of ARIMA and GMDH models in linear and nonlinear modeling. These two models are combined based on info entropy method. Experimental results with real data sets indicate that the proposed combined model can be an effective way to improve forecasting accuracy achieved by either of the models used separately.

关键词： ARIMA GMDH Combined Forecast Model Info Entropy Method

作者: Aiyun Zheng Weimin Liu Fanggeng Zhao

作者单位: School of Mechanical Engineering, Hebei Polytechnic University, Tangshan, 063009 Vehicle Management Institute, Bengbu 233011

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 1820-1824

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）