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Mangiarotti Sylvain, Coudret R., Drapeau Laurent, Jarlan Lionel. (2012). Polynomial search and global modeling: Two algorithms for modeling chaos. Physical Review E, 86 (4), p. 046205. ISSN 1539-3755.

Titre du document
Polynomial search and global modeling: Two algorithms for modeling chaos
Année de publication
2012
Type de document
Article référencé dans le Web of Science WOS:000309588800002
Auteurs
Mangiarotti Sylvain, Coudret R., Drapeau Laurent, Jarlan Lionel
Source
Physical Review E, 2012, 86 (4), p. 046205 ISSN 1539-3755
Global modeling aims to build mathematical models of concise description. Polynomial Model Search (PoMoS) and Global Modeling (GloMo) are two complementary algorithms (freely downloadable at the following address: http://www.cesbio.ups-tlse.fr/us/pomos_et_glomo.html) designed for the modeling of observed dynamical systems based on a small set of time series. Models considered in these algorithms are based on ordinary differential equations built on a polynomial formulation. More specifically, PoMoS aims at finding polynomial formulations from a given set of 1 to N time series, whereas GloMo is designed for single time series and aims to identify the parameters for a selected structure. GloMo also provides basic features to visualize integrated trajectories and to characterize their structure when it is simple enough: One allows for drawing the first return map for a chosen Poincare section in the reconstructed space; another one computes the Lyapunov exponent along the trajectory. In the present paper, global modeling from single time series is considered. A description of the algorithms is given and three examples are provided. The first example is based on the three variables of the Rossler attractor. The second one comes from an experimental analysis of the copper electrodissolution in phosphoric acid for which a less parsimonious global model was obtained in a previous study. The third example is an exploratory case and concerns the cycle of rainfed wheat under semiarid climatic conditions as observed through a vegetation index derived from a spatial sensor.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
Identifiant IRD
PAR00009439
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