Energy-based predictions in Lorenz system by a unified formalism and neural network modelling

Autor: A. Pasini, R. Langone, F. Maimone, V. Pelino
Jazyk: angličtina
Rok vydání: 2010
Předmět:
Zdroj: Nonlinear Processes in Geophysics, Vol 17, Iss 6, Pp 809-815 (2010)
Druh dokumentu: article
ISSN: 1023-5809
1607-7946
DOI: 10.5194/npg-17-809-2010
Popis: In the framework of a unified formalism for Kolmogorov-Lorenz systems, predictions of times of regime transitions in the classical Lorenz model can be successfully achieved by considering orbits characterised by energy or Casimir maxima. However, little uncertainties in the starting energy usually lead to high uncertainties in the return energy, so precluding the chance of accurate multi-step forecasts. In this paper, the problem of obtaining good forecasts of maximum return energy is faced by means of a neural network model. The results of its application show promising results.
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