Hi everyone, how do I fix this issue/>>>>>>Array indices must be positive integers or logical values.

clear all

clc

% Initialization Phase

N = 4;%from paper

Xmin1 = -5;%define Xmin

Xmax1 = 3;%define Xmax

Xmin2 = -3;%define Xmin

Xmax2 = 7;%define Xmax

Xmin3 = -1;%define Xmin

Xmax3 = 8;%define Xmax

T = 100;%Define max iteration

%fitness1=zeros(1,T);

fitness=zeros(1,T);

bestfitness=zeros(1,T);

bestfitness(1,1)=0;

%Initializing Y1-Y4

Y1 = zeros(1, N);

Y1(1:4) = Xmin1 + rand(1, 4) * (Xmax1 - Xmin1);

disp(['Initial Y1 values: ' num2str(Y1(1:4))]);

Y2 = zeros(1, N);

Y2(1:4) = Xmin2 + rand(1, 4) * (Xmax2 - Xmin2);

disp(['Initial Y2 values: ' num2str(Y2(1:4))]);

Y3 = zeros(1, N);

Y3(1:4) = Xmin3 + rand(1, 4) * (Xmax3 - Xmin3);

disp(['Initial Y3 values: ' num2str(Y3(1:4))]);

Xbest1 = zeros(1, T);% Initialize Xbest as an array

Xbest2 = zeros(1, T);

Xbest3 = zeros(1, T);

%X1 = zeros(1, T);

%X2 = zeros(1, T);

%X3 = zeros(1, T);

Xbar1 = zeros(1, T);

Xbar2 = zeros(1, T);

Xbar3 = zeros(1, T);

X1 = Xmin1 + rand() * (Xmax1 - Xmin1);

X2 = Xmin2 + rand() * (Xmax2 - Xmin2);

X3 = Xmin3 + rand() * (Xmax3 - Xmin3);

%Xbest(1) = min(Y); % Assign the minimum fitness value of the 4 Intial values as XBest

fprintf('X1 = %f\n', X1);

fprintf('X2 = %f\n', X2);

fprintf('X3 = %f\n', X3);

fitness1= (X1(1,1) - 1).^2 + (X2(1) - 2).^2 + (X3(1) - 3).^2;

fprintf('fitness1 = %f\n', fitness1);

Xbest1(1)=X1;

Xbest2(1)=X2;

Xbest3(1)=X3;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% While not max iteration

t = 2;

while t < T+1

%Measurement Phase

%for t = 1:N

d = rand(1, N);

%fprintf('d = %f\n', d);

for i = 1:N

if d(i) > 0.5

delta1 = (exp(-10 * t / T) * ((Xmax1 - Xmin1)) / 2);

delta2 = (exp(-10 * t / T) * ((Xmax2 - Xmin2)) / 2);

delta3 = (exp(-10 * t / T) * ((Xmax3 - Xmin3)) / 2);

Y1(t) = Xbest1(t-1) + ((-delta1) + rand() * (delta1- (-delta1)));

Y2(t) = Xbest2(t-1) + ((-delta2) + rand() * (delta2 - (-delta2)));

Y3(t) = Xbest3(t-1) + ((-delta3) + rand() * (delta3 - (-delta3)));

else

Y1(t) = Xbest1(t-1);

clear all

clc

% Initialization Phase

N = 4;%from paper

Xmin1 = -5;%define Xmin

Xmax1 = 3;%define Xmax

Xmin2 = -3;%define Xmin

Xmax2 = 7;%define Xmax

Xmin3 = -1;%define Xmin

Xmax3 = 8;%define Xmax

T = 100;%Define max iteration

%fitness1=zeros(1,T);

fitness=zeros(1,T);

bestfitness=zeros(1,T);

bestfitness(1,1)=0;

%Initializing Y1-Y4

Y1 = zeros(1, N);

Y1(1:4) = Xmin1 + rand(1, 4) * (Xmax1 - Xmin1);

disp(['Initial Y1 values: ' num2str(Y1(1:4))]);

Y2 = zeros(1, N);

Y2(1:4) = Xmin2 + rand(1, 4) * (Xmax2 - Xmin2);

disp(['Initial Y2 values: ' num2str(Y2(1:4))]);

Y3 = zeros(1, N);

Y3(1:4) = Xmin3 + rand(1, 4) * (Xmax3 - Xmin3);

disp(['Initial Y3 values: ' num2str(Y3(1:4))]);

Xbest1 = zeros(1, T);% Initialize Xbest as an array

Xbest2 = zeros(1, T);

Xbest3 = zeros(1, T);

%X1 = zeros(1, T);

%X2 = zeros(1, T);

%X3 = zeros(1, T);

Xbar1 = zeros(1, T);

Xbar2 = zeros(1, T);

Xbar3 = zeros(1, T);

X1 = Xmin1 + rand() * (Xmax1 - Xmin1);

X2 = Xmin2 + rand() * (Xmax2 - Xmin2);

X3 = Xmin3 + rand() * (Xmax3 - Xmin3);

%Xbest(1) = min(Y); % Assign the minimum fitness value of the 4 Intial values as XBest

fprintf('X1 = %f\n', X1);

fprintf('X2 = %f\n', X2);

fprintf('X3 = %f\n', X3);

fitness1= (X1(1,1) - 1).^2 + (X2(1) - 2).^2 + (X3(1) - 3).^2;

fprintf('fitness1 = %f\n', fitness1);

Xbest1(1)=X1;

Xbest2(1)=X2;

Xbest3(1)=X3;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% While not max iteration

t = 2;

while t < T+1

%Measurement Phase

%for t = 1:N

d = rand(1, N);

%fprintf('d = %f\n', d);

for i = 1:N

if d(i) > 0.5

delta1 = (exp(-10 * t / T) * ((Xmax1 - Xmin1)) / 2);

delta2 = (exp(-10 * t / T) * ((Xmax2 - Xmin2)) / 2);

delta3 = (exp(-10 * t / T) * ((Xmax3 - Xmin3)) / 2);

Y1(t) = Xbest1(t-1) + ((-delta1) + rand() * (delta1- (-delta1)));

Y2(t) = Xbest2(t-1) + ((-delta2) + rand() * (delta2 - (-delta2)));

Y3(t) = Xbest3(t-1) + ((-delta3) + rand() * (delta3 - (-delta3)));

else

Y1(t) = Xbest1(t-1);

Y2(t) = Xbest2(t-1);

Y3(t) = Xbest3(t-1);

end

end

%end

% Estimation Phase

% Initial Estimation

for k=2:t

if Y1(t - N + 1) < Y1(t - N + 2)

Xbar1(k) = Y1(t - N + 1) + (t - N + 2) - Y1(t - N + 1) * rand();

else

Xbar1(k) = Y1(t - N + 2) + (t - N + 1) - Y1(t - N + 2) * rand();

end

if Y2(t - N + 1) < Y2(t - N + 2)

Xbar2(k) = Y2(t - N + 1) + (t - N + 2) - Y2(t - N + 1) * rand();

else

Xbar2(k) = Y2(t - N + 2) + (t - N + 1) - Y2(t - N + 2) * rand();

end

if Y3(t - N + 1) < Y3(t - N + 2)

Xbar3(k) = Y3(t - N + 1) + (t - N + 2) - Y3(t - N + 1) * rand();

else

Xbar3(k) = Y3(t - N + 2) + (t - N + 1) - Y3(t - N + 2) * rand();

end

end

for k = 3:N

Xbar1(k) = Xbar1(k - 1) + (1/k) * (Y1(t - N + k) - Xbar1(k - 1));

Xbar2(k) = Xbar2(k - 1) + (1/k) * (Y2(t - N + k) - Xbar2(k - 1));

Xbar3(k) = Xbar3(k - 1) + (1/k) * (Y3(t - N + k) - Xbar3(k - 1));

end

X1(t) = Xbar1(k); % Update X(t) as X(k)

X2(t) = Xbar2(k); % Update X(t) as X(k)

X3(t) = Xbar3(k); % Update X(t) as X(k)

%Evaluation Phase

% Fitness evaluation

fitness(1,t) = (X1(t) - 1).^2 + (X2(t) - 2).^2 + (X3(t) - 3).^2;

fprintf('fitness = %f\n', fitness(1,1));

% Update bestfitness and Xbest

if fitness(1,t) > bestfitness(1,t-1)

bestfitness(1,t) = fitness(1,t);

Xbest1(1,t) = X1(1,t);

Xbest2(1,t) = X2(1,t);

Xbest3(1,t) = X3(1,t);

else

bestfitness(1,t) = fitness(1,t-1);

Xbest1(1,t) = Xbest1(1,t-1);

Xbest2(1,t) = Xbest1(1,t-1);

Xbest3(1,t) = Xbest1(1,t-1);

end

t=t+1;

end

Xbest1;

Xbest2;

Xbest3; + (t - N + 1) - Y1(t - N + 2) * rand();

end

if Y2(t - N + 1) < Y2(t - N + 2)

Xbar2(k) = Y2(t - N + 1) + (t - N + 2) - Y2(t - N + 1) * rand();

else

Xbar2(k) = Y2(t - N + 2) + (t - N + 1) - Y2(t - N + 2) * rand();

end

if Y3(t - N + 1) < Y3(t - N + 2)

Xbar3(k) = Y3(t - N + 1) + (t - N + 2) - Y3(t - N + 1) * rand();

else

Xbar3(k) = Y3(t - N + 2) + (t - N + 1) - Y3(t - N + 2) * rand();

end

end

for k = 3:N

Xbar1(k) = Xbar1(k - 1) + (1/k) * (Y1(t - N + k) - Xbar1(k - 1));

Xbar2(k) = Xbar2(k - 1) + (1/k) * (Y2(t - N + k) - Xbar2(k - 1));

Xbar3(k) = Xbar3(k - 1) + (1/k) * (Y3(t - N + k) - Xbar3(k - 1));

end

X1(t) = Xbar1(k); % Update X(t) as X(k)

X2(t) = Xbar2(k); % Update X(t) as X(k)

X3(t) = Xbar3(k); % Update X(t) as X(k)

%Evaluation Phase

% Fitness evaluation

fitness(1,t) = (X1(t) - 1).^2 + (X2(t) - 2).^2 + (X3(t) - 3).^2;

fprintf('fitness = %f\n', fitness(1,1));

% Update bestfitness and Xbest

if fitness(1,t) > bestfitness(1,t-1)

bestfitness(1,t) = fitness(1,t);

Xbest1(1,t) = X1(1,t);

Xbest2(1,t) = X2(1,t);

Xbest3(1,t) = X3(1,t);

else

bestfitness(1,t) = fitness(1,t-1);

Xbest1(1,t) = Xbest1(1,t-1);

Xbest2(1,t) = Xbest1(1,t-1);

Xbest3(1,t) = Xbest1(1,t-1);

end

t=t+1;

end

Xbest1;

Xbest2;

Xbest3;

Error in Untitled (line 150)

if Y1(t - N + 1) < Y1(t - N + 2)

I also need Y values in an array of 4###

Answer 1

[Image Analyst]

Since this is one of the most common FAQs, see the FAQ for a thorough discussion:

https://matlab.fandom.com/wiki/FAQ#.22Subscript_indices_must_either_be_real_positive_integers_or_logicals..22