关于水文时间序列预报的可能性

V. Artemenko, Volodymyr Petrovych
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引用次数: 0

摘要

提出了用确定性混沌动力学方法预测自然时间序列(水文时间序列)的方法。对时间序列的分析揭示了原始数据隐藏的规律。下文揭示了用于实现输入数据预测的规律。水文时间序列或作为混沌时间序列,只能在确定的数步向前预测。水文时间序列存在预测极限(预测视界)。除非超出预测范围,否则同样的预测是可能的。工作的目的是设计程序,研究自然时间序列对预测可能性的影响。由于原始数据使用的是乌克兰大平坦河流(长度为4*365点)的平均日消费量数据。对于自然时间序列的预测,采用了局部逼近法的自适应修正。时间序列的预测范围是通过因子线性相关来定义的(关于多少点向前(最大)可能预测时间序列以保持因子相关性在0.7…1.0范围内)。从参数DIM(维数重构相空间)中探索了预测层的依赖关系。研究结果表明,对于时间序列(水文)的基本决定论-时间序列预测在15…22点以后。软件设计用于调查自然时间序列(水文和水化学)进行预测(寻找预测水平)。所呼吁的调查表明,局部逼近法比经典方法更有效的预测(经典方法的充分预测可能只在1…2点以后)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ABOUT OF FORECASTING POSSIBILITY OF HYDROLOGICAL TIME SERIES
It is offered forecast the natural time series (hydrological time series) by methods the deterministic chaotic dynamic. At analysis of the time series reveal the hidden regularities at raw data’s. Hereinafter revealled regularities use for realization of the forecast of input data. Hydrological time series either as chaotical time series possible forecast only at determined number step onward. For hydrological time series exists the limit of forecasting (forecasting horizon). The identical prediction possible unless come behind of the forecasting horizon. The aim of the work there is design of the procedure the investigations of the natural time series on possibility of the forecasting. As raw data’s were used the mean day data of consuption for the large flat river of the Ukraine (length is 4*365 points). For forecasting of the natural time series it was used designed an autors modification of the method of Local Approximation. The forecasting horizon of time series was defined by means of factor the linear correlation (on how much points onward (maximum) possible forecast the time series for conservation of the factor the correlation within the range of 0.7 … 1.0). The explored dependency of the forecasting horizon from parameter DIM (Dimensionality Reconstrusted the phase space). The results of the research say for essential determinism of time series (hydrological) – the time series is forecasted on 15 … 22 points onward. Software was designed for investigations of the natural time series (hydrological and hydrochemistry) for forecasting (to find forecasting horizon). The called on investigation has shown that the method of Local Approximation more efficient than classical methods the forecast (for classical methods the adequate forecast possible only on 1 … 2 points onward).
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