Try to improve the calibration of the population model by further modifying
the parameters a1 and
a2. You can either continue
the trial and error exercises or upload the model into Madonna and try
the curve-fitting in there. Do not forget to add the Error function to
the model since visual comparison becomes quite hard once we get really
close to the optimal solution. Is there a better combination of parameters
than a1 = a2 = 0.1?
I tried messing with the coefficients quite a bit, and I get the best performance with ain = 0.1 and aout = 0.11. The pink line is the error function, defined as 100*(Population-DATA)/Population.
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