Forecasting confined spatiotemporal chaos with genetic algorithms

被引：23

作者：

López, C ^{[1
]}

Alvarez, A

Hernández-García, E

机构：

[1] Univ Illes Balears, CSIC, Inst Mediterraneo Estud Avanzados, IMEDA, Palma de Mallorca 07071, Spain

[2] SACLANT Untersea Res Ctr, I-19138 San Bartolomeo, La Spezia, Italy

来源：

PHYSICAL REVIEW LETTERS | 2000年 / 85卷 / 11期

关键词：

D O I：

10.1103/PhysRevLett.85.2300

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

A technique to forecast spatiotemporal time series is presented. It uses a proper orthogonal or Karhunen-Loeve decomposition to encode large spatiotemporal data sets in a few time series, and genetic algorithms to efficiently extract dynamical rules from the data. The method works very well for confined systems displaying spatiotemporal chaos, as exemplified here by forecasting the evolution of the one-dimensional complex Ginzburg-Landau equation in a finite domain.

引用

页码：2300 / 2303

页数：4

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