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Dear All,
I need to optimize parameters of a function using the ga module. I have a coefficient matrix say A(9:4):
A =
-0.0996 -0.0323 -0.0640 -0.0365
0.0859 -0.0636 0.0552 0.0315
0.1805 0.0125 0.1159 0.0662
0.0521 0.0513 0.0335 0.0191
-0.3028 0.0647 -0.1946 -0.1111
-0.2242 -0.0382 -0.1440 -0.0822
0.0475 -0.0191 0.0305 0.0174
0.2170 -0.0010 0.1394 0.0796
0.0437 0.0257 0.0281 0.0160
and a vector B where i store the experimental data say B(9:1):
B =
-4.8700
-3.2100
5.1000
5.3400
-1.6200
-8.1700
-0.4700
4.8300
3.0800
my chromosome will be a vector x(4:1)
I would like to write a fitness function like:
fitnessfcn = abs((A*x)-B) [x,fval]=ga(fitnessfcn,4)
I have used the below function
FitnessFcn = @(x) abs( ((A(1,1)*x(:,1))+(A(1,2)*x(:,2))+(A(1,3)*x(:,3))+(A(1,4)*x(:,4)))-B(1,1))
which only uses (the first row of A) * (column x)-(first element of B)
How can I write in general form to use all the data. I have tried fitnessfcn = abs((A*x)-B) but it says Error using ==> mtimes Inner matrix dimensions must agree.
Do I have to use for loops and how to write a function with for loops?
I would really welcome any sugestion.
Kind regards, Christos
Réponse acceptée
Plus de réponses (3)
Star Strider
le 23 Juin 2012
If the fitness function is supposed to produce a scalar to be minimized, then I suggest something like:
FitnessFcn = @(A,B,x) ( sum( (A*x-B).^2 ) );
Since A is (9x4), x is (4x1) and B is (9x1), A*x will produce a (9x1) vector. A*x-B produces the error vector, and the FitnessFcn here will produce the sum of the squared errors, a scalar >= 0.
chris
le 11 Mai 2011
0 votes
chris
le 22 Juin 2012
0 votes
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