摘要
在介绍重构相空间技术的主要定量指标(关联维数D2和柯尔莫奇诺夫(Kolmogorov)熵)的基础上,针对长江上游川中地区降水时间序列,探讨了不同嵌入维m下其关联维数的变化规律。计算结果为该时间序列的饱和关联维D2=5.11,最低嵌入维m=10,Kolmogorov熵k=0.338;采用主分量分析(PCA分布)方法进一步验证了该序列具有混沌特性,并且得到该序列的预测年限不应超过2.96a,为降水预测提供了较为科学的依据。
Based on introducing the main quantitative indexes of correlation dimension D 2 and Kolmogorov entropy in rebuilding time series imbedding space, the relationship between built?in dimension m and correlation dimension D 2 is discussed with the precipitation time serial in Sichuan middle region of Yangtze River upstream. The saturation correlation dimension, minimum built?in dimension and Kolmogorov entropy are calculated and given, that is D 2=(5.11), m =10 and k =(0.338). Primary component analysis method is applied to validate its chaotic character, and obtained that the forecasting length for this precipitation time serial would not exceed (2.96) year. This time serial chaotic analysis will provide a scientific gist for precipitation forecasting.
出处
《长江科学院院报》
CSCD
北大核心
2004年第1期43-46,共4页
Journal of Changjiang River Scientific Research Institute
基金
国家高技术研究发展计划项目(2002AA6Z3263)
