Time Series Preprocessing and Forecasting Based on EMD

摘要：

　　In this paper we pay attention to the preprocessing of time series and its application.We apply Empirical Mode Decomposition (EMD) to decompose three kinds of series into their components in order to study the data and forecast more efficiently.We try to unite EMD analysis and autoregressive integrated moving average processes (ARIMA) into a new forecasting technique which we call EMD-ARIMA.We find that our method is extraordinarily close to the original data.

关键词： Empirical mode decomposition (EMD) detrended fluctuation analysis (DFA) autoregressive integrated moving average processes (ARIMA)

作者: Guochen Feng Pengjian Shang Xuejiao Wang

作者单位: School of Science,Beijing Jiaotong University,Beijing 100044,P R of China

会议类型: 国际会议

会议名称: 2012 2nd International conference on Machinery Electronics and Control Engineering (2012年第二届国际机械电子与控制工程会议(ICMECE 2012))

会议地点: 济南

会议语种:英文

页码: 1256-1261

在线出版日期: 2012-12-29（万方平台首次上网日期，不代表论文的发表时间）