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Given the distribution of population, the growth function of populated locations and the largest population size, we insert the above expressions of P s,t), l(t), and n(t) as shown in Eq. 4, Eq. 5 and Eq. 6 into Eq. 3. Then we have GP ( t ) = ∫ 1 a ∗ t b + c ( ( φ ∗ s - λ ) ∗ ( η ∗ t ε ) ∗ s ) ds = ηφ t ε 2 - λ [ ( a ∗ t b + c ) 2 - λ - 1 ].
Instead of numerating all population sizes, we use the proportion of the number of locations with population size s over the total number of populated locations, known as population distribution, which is denoted as P s, the total number of populated locations L and the largest population size N to construct the formulation of aggregated population: GP = ∑ s = 1 N P s ∗ L ∗ s, (2).
Similar to the analysis of populated location growth, the growth of the largest population size can also be fitted using a power function as the following: n ( t ) = a ∗ t b + c. (6) Figure 3 The population growth of the largest populated location.
The region also has the largest population size.
Therefore, the growth function of the largest population size is a power function.
To obtain n(t), we grab the largest population size from month to month in each data set and plot the growth of the largest population size as a function of time.
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Nonetheless, we capture countries with the largest population sizes.
In this case signal transmission is not improved by the large population size.
Larger population size and a stable environment make evolutionary change less likely now.
Thus, for higher number of generations and larger population size, the system has better performance.
They require the use of large population size and may suffer from slow convergence.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com