摘要
利用相空间重构技术,并借助G-P算法、C-C方法和Wolf方法从宁陵地区地下水位一维时间序列中提取Lyapunov指数,结果表明此时间序列具有混沌特征。计算了宁陵地区地下水位时间序列的关联维数、时间延迟和最大Lyapunov指数,将局域加权一阶多步预测模型应用于地下水位预测。预测表明,此模型可有效应用于地下水位时间序列的多步预测。
Applying phase space reconstruction method, G-P arithmetic, C-C arithmetic and Wolf method, this paper distills Lyapunov exponents from one-dimension time series of underground water table in Ningling county. The result indicates that this time series possesses the character of chaos. The correlation dimension of time series, time delay and the largest Lyapunov exponent of underground water table in Ningling county are calculated. The add-weighted one-rank multi-steps prediction model is developed for the prediction of underground water table. The prediction indicates that this model can be easily used in multi-steps prediction of underground water table time series
出处
《地球科学与环境学报》
CAS
2007年第1期66-69,共4页
Journal of Earth Sciences and Environment
基金
河南省杰出人才创新基金项目(04210005000)
关键词
时间序列
相空间重构
混沌
地下水位
LYAPUNOV指数
关联维数
time series
phase space reconstruction
chaos
underground water table
Lyapunov exponent
correlation dimension
