I am a student enrolled in the 2nd year physics Master's degree, i am a beginner in Matlab and i have the same problem like Mattias, can you help me and is it was possible to get your e-mail.
My problem is to make a fit of a nonlinear equation to data with the genetic algorithm and to minimize R, my model function is
The industrial data Rexp and t are known: these are two vectors that give the variation of Rexp as a function of time (t)
rate also is known and equal to 40
I declared my function (fitnes function) as follows:
t=[0 2 4 6 8 10 12 14 16 18 20 22 24 26 28];
Rexp=[1 .7987e-05 3.07996e-05 3.90531e-05 1.89562e-05 2.82794e-05 5.55377e-05
4.75723e-05 6.2447e-05 5.35282e-05 5.16775e-05 4.67144e-05 4.63215e-05 6.62753e-05
S (i) = sum ((Rexp (i) -R * (1-exp (-t (i) ./ 40))) ^ 2)
I use it in the methods of Gauss Newton and Levenberg marquardt and I got a good result of R which is in the order of 0.000059 but with the genetic algorithm I found no result.