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As it can be appreciated in Figure 1, the vaccinated, exposed, infected, and removed-by-immunity (or "immune" or "recovered") population converge to zero and cannot be distinguished in the figure.
Figures 3-6 show the dependence of the dynamic behavior of system (1.2) on the harvesting efforts for the prey E 1. Figures 3-6 show that when E 1 is small, both the prey and predator population converge to their equilibrium values respectively, but as E 1 is large, the predator does not have enough food and approaches extermination at last.
Perceptions about risk and actual behavioural risk in the ACB population converge in some areas, and diverge in others.
The aim of the algorithm is to make the population converge to a final population in which the best performing individuals will be as close as possible to the optimal solution of the problem.
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(ii)The fitness of the population converges and ceases to improve.
On the one hand, the removed-by-immunity population converges asymptotically to the total population as time tends to infinity.
This technique prevents the population converging to the local optimum and directs the same to the global optimum.
As the evolutionary process matures, the population converges to a small region and the perturbations adaptively become small.
Evolutionary multi-criterion optimization (EMO) algorithms emphasize non-dominated and less crowded solutions in a population iteratively until the population converges close to the Pareto optimal set.
Also, the susceptible population converges to zero while the removed-by-immunity population tracks asymptotically the whole population as time tends to infinity.
Concerning step 6b, after the population converges to a prescribed measure, it is important to introduce new strings based on either genotype convergence of phenotype convergence, or based on the occurrence of a fixed number of generations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com