Using synchronization to improve the forecasting of large relaxations in a cellular-automaton model

Autor:	Amalio F. Pacheco, Javier B. Gómez, M. Vázquez-Prada, Alvaro Gonzalez
Rok vydání:	2004
Předmět:	Dynamical systems theory Computer science Event (relativity) Pattern recognition (psychology) SIGNAL (programming language) General Physics and Astronomy State (computer science) Algorithm Cellular automaton Synchronization Physics::Geophysics Power (physics)
Zdroj:	Europhysics Letters (EPL). 68:611-617
ISSN:	1286-4854 0295-5075
Popis:	A new forecasting strategy for stochastic systems is introduced. It is inspired by the concept of anticipated synchronization between pairs of chaotic oscillators, recently developed in the area of Dynamical Systems, and by the earthquake forecasting algorithms in which different pattern recognition functions are used for identifying seismic premonitory phenomena. In the new strategy, copies (clones) of the original system (the master) are defined, and they are driven using rules that tend to synchronize them with the master dynamics. The observation of definite patterns in the state of the clones is the signal for connecting an alarm in the original system that efficiently marks the impending occurrence of a catastrophic event. The power of this method is quantitatively illustrated by forecasting the occurrence of characteristic earthquakes in the so-called Minimalist Model.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::836f9a8c0633a5a846f7ec1f3f306e20 https://doi.org/10.1209/epl/i2004-10269-3 Zobrazit plný text záznamu