INDEX EXCEED NUMBER OF ARAY in GAPSO optimization of simulink model?

Hello there,

I downloaded a GAPSO zip code to tune simulink parameters. but the following problem appeared even if I tried repeatdly

may anyone help me?'.............

• Index exceeds the number of array elements (100).
• Error in GAPSO (line 54)
• gpop=pop(index);

..nvar=18;

% ub=[6.8 265 49 65 400 60 3.5 17 17 5.5 15 70 4.5 30 15 3.8 16.2 14.2]; %Upper Bound

% lb=[2.5 255 42 40 300 40 1.5 10 12 2.5 11 55 0 18 5 0 8 5]; %Lower Bound

lb.v=-5;

ub.v=5;

popsize=100;

maxiter=500;

pc=0.9;

ncross=2*round((popsize*pc)/2);

pm=1-pc;

nmut=round(popsize*pm);

W=1;

C1=2;

C2=2;

W_RF=0.97;

%% initial population algorithm

tic

emp.Obj=[];

emp.PObj=[];

emp.v=[];

pop=repmat(emp,popsize,1);

for i=1:popsize

pop(i).Obj=lb.var+rand(1,nvar).*(ub.var-lb.var);

pop(i).PObj= STSMC_Parameters(pop(i).Obj);

pop(i).v=0;

end

[value,index]=min([pop.PObj]);

gpop=pop(index); %$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Line 54

bpop=pop;

%% main loop algorithm

BEST=zeros(maxiter,1);

MEAN = zeros(maxiter,1);

for iter=1:maxiter

% PSO

PSOpop=PSOfunc(pop,bpop,W,C1,C2,nvar,lb,ub);

% crossover

crosspop=repmat(emp,ncross,1);

crosspop=crossover(crosspop,pop,ncross);

% mutation

mutpop=repmat(emp,nmut,1);

mutpop=mutation(mutpop,pop,nvar,nmut,popsize,lb,ub);

[pop]=[pop;PSOpop;crosspop;mutpop];

[value,index]=sort([pop.PObj]);

pop=pop(index);

gpop=pop(1);

pop=pop(1:popsize);

BEST(iter)=gpop.PObj;

MEAN(iter)=mean([pop.PObj]);

disp([' Iter = ', num2str(iter) ' BEST = ' ,num2str(BEST(iter))])

W=W*W_RF;

end

%% results algorithm

disp([ ' Best Solution = ' num2str(gpop.Obj)])

disp([ ' Best Fitness = ' num2str(gpop.PObj)])

disp([ ' MEAN = ' num2str(mean([pop.PObj]))])

disp([ ' Time = ' num2str(toc)])

figure(1)

plot(BEST(1:iter),'r','LineWidth',1.25);

hold on

plot(MEAN(1:iter),'b-.','LineWidth',1.25);

xlabel('iteration')

ylabel(' best solution')

legend(' BEST, PSO&GA' , 'MEAN, PSO&GA')

%title('PSO&GA')

%plot(BEST,'r')

%xlabel('Iteration')

%ylabel('Fitness')

%egend('BEST')

%title('GAPSO')

Answer 1

[Samay Sagar]

The error message suggests that the class names for your SVM classification are not found in the input labels. In your code, you are using the fitcsvm function with the 'ClassNames' parameter set to [1, 2], which implies that your class labels should be 1 and 2.However, it seems that your trainClusters variable contains cluster indices rather than class labels. To resolve this issue, you can convert the cluster indices to class labels before fitting the SVM model.