Those fitting functions are nonlinear functions, which means that the optimization process will have amounts of calculation time, in order to ensure the accurate, uniform distribution of the optimization objective function value and save the operation time as much as possible. Finally, we determined the genetic algorithm optimization parameters as shown in Table 5.

Table 5

Genetic algorithm parameters.

ParametersOptimal individual coefficientPopulation sizeMaximum evolutionary algebraStop algebraFitness function deviation
Values 0.3 100 200 200 10−8 
ParametersOptimal individual coefficientPopulation sizeMaximum evolutionary algebraStop algebraFitness function deviation
Values 0.3 100 200 200 10−8 

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