Fitting a function to data (fminsearch) with limits
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loes visser
el 30 de Ag. de 2016
Respondida: Stefan Schuberth
el 8 de Nov. de 2022
Hey!
I try to fit a model to measured data. I already got a real close with the fminsearch option. However, I know the model will never fit completly to the measured data. I know the range wherein the unknown factors should be, how can I include this in the function.
This is a part of my code;
p= [0.31;114;3.5];
y2=fitfunc(TempZone1day,TempZone2day,TempZone3day,TempZone4day,TempZone5day,buitenTempday,FlowZone1day,FlowZone2day,FlowZone3day,FlowZone4day,KNMIwindday,SMA,p);
figure(1)
plot(tijd,WarmteCvday,'+',tijd,y2,'-')
a0=p;
aBest = fminsearch(@(a) SumErrfun1(a,TempZone1day,TempZone2day,TempZone3day,TempZone4day,TempZone5day,buitenTempday,FlowZone1day,FlowZone2day,FlowZone3day,FlowZone4day,KNMIwindday,SMA,WarmteCvday,tijd),a0);
disp(aBest)
For example, I know that p(1) should be within 0.1-0.5, p(2) within 100-200 and p(3) within 2-6. Because now aBest (the best combination) is [-0.0328; 61.8202; 0.4375], which is not even a possible option. How can I include these ranges?
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John D'Errico
el 30 de Ag. de 2016
Editada: John D'Errico
el 30 de Ag. de 2016
fminsearch has no capability to take bounds on the search. If the objective is such that a better result lies outside of where you want it, too bad. :)
Having said that, you can use fminsearchbnd , a tool found on the file exchange. It does allow bounds on the variables. Just download and install that tool on your search path, then use it instead.
Más respuestas (3)
Jie Jian
el 9 de En. de 2020
Or you can use the function 'mapping_parameters.m' to transfer unbounded parameters to bounded ones
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kursat cihan
el 30 de Ag. de 2020
John D'Errico....much love from Germany, helped me a lot!!!
Bachelor Thesis in Material Modelling, used it for a parameter optimization in bringing simulations together with experimental data...PEACE
1 comentario
Stefan Schuberth
el 8 de Nov. de 2022
you can use q=f1*atan(p)+f2 to construct a limited parameter q from an unlimited parameter p :)
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