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| Titel |
Energy-based predictions in Lorenz system by a unified formalism and neural network modelling |
| VerfasserIn |
A. Pasini, R. Langone, F. Maimone, V. Pelino |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 17, no. 6 ; Nr. 17, no. 6 (2010-12-23), S.809-815 |
| Datensatznummer |
250013767
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| Publikation (Nr.) |
 copernicus.org/npg-17-809-2010.pdf |
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| Zusammenfassung |
| 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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