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Regularity analysis of an individual-based ecosystem simulation
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10.1063/1.3514011
/content/aip/journal/chaos/20/4/10.1063/1.3514011
http://aip.metastore.ingenta.com/content/aip/journal/chaos/20/4/10.1063/1.3514011
View: Figures

Figures

Image of FIG. 1.
FIG. 1.

A simple fuzzy cognitive map for detection of foe and decision to evade with its corresponding matrix L and 0 for “foe close,” 1 for “foe far,” 2 for “fear,” and 3 for “evasion,” and the fuzzification and defuzzification functions.

Image of FIG. 2.
FIG. 2.

Population of prey and predator agents.

Image of FIG. 3.
FIG. 3.

Evolution of the prey and predator species.

Image of FIG. 4.
FIG. 4.

Intersection between the flow and the Poincaré section generating the set of points .

Image of FIG. 5.
FIG. 5.

Intersection of time series trajectory and Poincaré section.

Image of FIG. 6.
FIG. 6.

Applying of P&H method over Lorenz time series and random time series.

Image of FIG. 7.
FIG. 7.

Prediction error for experimental data vs the number of time steps . The slope of the solid line in the intermediate range of gives the largest Lyapunov exponent .

Image of FIG. 8.
FIG. 8.

The results of hypothesis testing using 24 surrogate data sets for random time series (left) and Lorenz time series (right) using Higuchi fractal dimension.

Image of FIG. 9.
FIG. 9.

The results of hypothesis testing using 24 surrogate data sets over simulation’s population time series; (a) prey and (b) predator using Higuchi fractal dimension.

Image of FIG. 10.
FIG. 10.

The results of hypothesis testing using 24 surrogate data sets over simulation’s population time series; (a) prey and (b) predator series using correlation dimension

Image of FIG. 11.
FIG. 11.

The results of hypothesis testing using 24 surrogate data sets for random time series (left) and Lorenz time series (right) using largest Lyapunov exponent.

Image of FIG. 12.
FIG. 12.

The results of hypothesis testing using 24 surrogate data sets over simulation’s population time series; (a) prey and (b) predator series using largest Lyapunov exponent.

Image of FIG. 13.
FIG. 13.

The results of hypothesis testing using 24 surrogate data sets over simulation’s population time series; (a) prey and (b) predator using P&H method.

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/content/aip/journal/chaos/20/4/10.1063/1.3514011
2010-11-18
2014-04-25
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Regularity analysis of an individual-based ecosystem simulation
http://aip.metastore.ingenta.com/content/aip/journal/chaos/20/4/10.1063/1.3514011
10.1063/1.3514011
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