Logistic Growth

introduction - exponential growth

introduction - biology

article - New York Times

unlimited growth and decay

growth - eaxample bacteria small

$${N(t) = N_0 \cdot \mathrm{e}^{kt}}$$

$N_0$: the initial amount at $t=0$.

time for initial amount to double - Verdopplungszeit

$T_2 = \frac{\ln 2}{k}, \,\, k>0$

radioactive decay small

$${N(t) = N_0 \cdot \mathrm{e}^{-kt}}$$

$N_0$: the initial amount at $t=0$.

half-life - Halbwertszeit

$T_{\frac{1}{2}} = \frac{\ln (\frac{1}{2})}{-k}, \,\, k>0$

limited growth small

$${N(t) = a + b \cdot \mathrm{e}^{-kt}}$$

where $k>0$

$N_0 = a + b$: the initial amount.

$a$: the maximum possible amount as $t \rightarrow \infty$

limited decay - Newton’s equation of cooling small

$${T(t) = T_U + c \cdot \mathrm{e}^{-kt}}$$

where $k>0$

$c = T_0 - T_U$

$T_0$ : the initial temperature at $t=0$

$T_U$ : temperature of the environment (Umgebungstemperatur) $t \rightarrow \infty$

combining the two - logistic growth

small

the logistic function in general terms

The logistic function N(t) is described by the parameters a, b and k. You can find the first and second derivative by using the quotient rule and the chain rule.

$${N(t) = \frac{a}{1 + b \cdot \mathrm{e}^{-kt}}}$$

where $k>0$

$N_0 = \frac{a}{1 + b}$: the initial amount.

$G = a$: the maximum possible amount as $t \rightarrow \infty$ (Grenzbestand)

$W$ : the point of inflexion - der Wendepunkt (maximum gradient / maximale Steigung)

the first and second derivative

$${N^\prime (t) = \frac{abk \cdot \mathrm{e}^{-kt}}{(1 + b \cdot \mathrm{e}^{-kt})^2}}$$

$${N^{\prime\prime} (t) = \frac{-abk^2 \cdot \mathrm{e}^{-kt} \left( 1 - b\mathrm{e}^{-kt}\right)}{(1 + b \cdot \mathrm{e}^{-kt})^3}}$$

other form

$${N(t) = \frac{N_0 \cdot G}{N_0 + (G - N_0) \cdot \mathrm{e}^{-Gkt}}}$$

logistic curve

the logistic curve is referred to as a common S-shaped curve (alos known as a sigmoid curve)

applications in biology

Khan academy - applications to biology


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