A computational framework for finding parameter sets associated with chaotic dynamics

Many biological ecosystems exhibit chaotic behavior, demonstrated either analytically using parameter choices in an associated dynamical systems model or empirically through analysis of experimental data. In this paper, we use existing software tools (COPASI, R) to explore dynamical systems and unco...

Full description

Saved in:
Bibliographic Details
Published inIn silico biology Vol. 14; no. 1-2; pp. 41 - 51
Main Authors Koshy-Chenthittayil, S., Dimitrova, E., Jenkins, E.W., Dean, B.C.
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 28.05.2021
IOS Press
Subjects
Algorithms
Ecosystem
Nonlinear Dynamics
genetic algorithm
Chaotic dynamics
parallel coordinate plot
population dynamics
Lyapunov exponent
Online AccessGet full text

Cover

More Information
Summary:Many biological ecosystems exhibit chaotic behavior, demonstrated either analytically using parameter choices in an associated dynamical systems model or empirically through analysis of experimental data. In this paper, we use existing software tools (COPASI, R) to explore dynamical systems and uncover regions with positive Lyapunov exponents where thus chaos exists. We evaluate the ability of the software’s optimization algorithms to find these positive values with several dynamical systems used to model biological populations. The algorithms have been able to identify parameter sets which lead to positive Lyapunov exponents, even when those exponents lie in regions with small support. For one of the examined systems, we observed that positive Lyapunov exponents were not uncovered when executing a search over the parameter space with small spacings between values of the independent variables.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1386-6338
1434-3207
DOI:10.3233/ISB-200476