require_once JPATH_SITE.'/TTcustom/TT_contentparser.php';
\(parameters = array("topicname" => "math",
 "modelname" => "Series_Numbers/ejss_model_e_LogisticMap_R");

echo generateSimHTML(\)parameters, "EJSS");

For Teachers

The Logistic Map is used to model population growth using the following equation: x(n+1) = rx(n)(1 - x(n))

Where x represents the ratio of the existing population to the maximum possible population, n represents the number of iterations, and r is a parameter ranging between 0 and 4 that changes the behaviour of the population growth.

In this simulation, we denote the parameter r by 4r, where r now ranges between 0 and 1. From here on, when we refer to r, we mean the r in the simulation that ranges between 0 and 1.

This model simulates the effects of reproduction, where the population size increases at a rate proportional to the current population when the population is small, and starvation, where the population size decreases at a rate proportional to the carrying capacity of the environment.

It is not decisive for the bifurcation that the limiting term is exactly (1-x(n)). The crucial point is the non-linearity of the conjunction x(n) -x(n)^2.

To demonstrate this, a generalized series rule is used in this simulation, using a term (1-x(n)^k), with k > 0 :
x(n+1) = 4rx(n)(1-x(n)^k)

When r is approximately 0.89 to 1, the population size starts to exhibit chaotic behaviour, fluctuating wildly between many values. In fact, the Logistic Map is commonly used to show how chaotic systems can arise from seemingly simple models.

Author : Francisco Esquembre and Wolfgang Christian, JavaScript version Wei Chiong and Loo Kang
Text and original idea from the Open Source Physics project manual
Date : July 2003 and JavaScript 2018





Other Resources


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