A novel approach in predicting non-stationary time series by combining external forces  

作　　者：WANG GeLi YANG PeiCai BIAN JianChun ZHOU XiuJi 

机构地区：[1]Laboratory for Middle Atmosphere and Glotal Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences Beijing 100029, China [2]Chinese Academy of Meteorological Sciences, Beijing 100081, China [3]State Key Laboratory of Severe Weather, Beijing 100081, China

出　　处：《Chinese Science Bulletin》2011年第28期3053-3056,共4页

基　　金：the National Natural Science Foundation of China (40890052, 41075061 and 40940023)

摘　　要：In this paper, we investigate a novel technique that reconstructs the observed time series and incorporates driving forces. Furthermore, to illustrate and test the technique, we consider a couple of predictive experiments using ideal time series provided by the logistic and Lorenz systems with specific driving forces. The preliminary results show this approach can improve prediction proficiency to some extent, and the external forces play a similar role to that of state variables.In this paper, we investigate a novel technique that reconstructs the observed time series and incorporates driving forces. Furthermore, to illustrate and test the technique, we consider a couple of predictive experiments using ideal time series provided by the logistic and Lorenz systems with specific driving forces. The preliminary results show this approach can improve prediction proficiency to some extent, and the external forces play a similar role to that of state variables.

关 键 词：时间序列预测 非平稳 LORENZ系统 测试技术 预测能力 状态变量 驱动力 理想 

分 类 号：O415.5[理学—理论物理] TP183[理学—物理]