this two code are connected to each other when i run the first code it gives me error says: Error using GWO Too many output arguments.

Question

essrra 2023-3-13

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1928090-this-two-code-are-connected-to-each-other-when-i-run-the-first-code-it-gives-me-error-says-error-us

评论： Walter Roberson 2023-3-15

close all
clear all
clc
global A trn vald ;
T=100;
N=30;
lb=0;%
ub=1;
runs=30;
threshold=2;
fitfun=@AccSz; %fitness function 0.99Err+0.01*Selection Ratio
%% Problem Definition
fn={'arrhythmia','primary-tumor','australian','base_Brain_T91','hepatitis','horse-colic',...
    'KrvskpEW','BreastEW','spambase','SportsArticles','WaveformEW',...
    'WineEW','Zoo','CongressEW','Exactly','Exactly2','HeartEW','IonosphereEW','Lymphography'...
    'M-of-n','PenglungEW','SonarEW','SpectEW','Vote'};
SD=size(fn,1);
for j=1:SD
    libb=['BDD\' cell2mat(fn(j)) '.mat'];
   
   
% A=load('C:\Users\d\Downloads\archieve');
   % save('featuresall.mat')
        load('f')
 A=featuresall;
    nVar=size(featuresall,2)-1;
    
    r=randperm(size(featuresall,1));
    trn=r(1:floor(length(r)*0.8));  % split 80% train 20% test not k-fold
    vald=r(floor(length(r)*0.8)+1:end);
    
    dim=nVar;
    for i=1:runs
        display(['At run ', num2str(i)]);
        [t_GWO(i),Nf_GWO(i),outcome_GWO(i),best_GWO(i,:),GWO_conv(i,:)]=GWO(N,T,lb,ub,dim,fitfun);
        [acc_GWO(i),sensi_GWO(i),speci_GWO(i)]=Acc(best_GWO(i,:));
end
str=(strcat(char(fn{j}),'_',num2str(1)));
    save(str)
end
Error using load
Unable to find file or directory 'f'.
%___________________________________________________________________%
%  Grey Wolf Optimizer (GWO) source codes version 1.0               %
%                                                                   %
%  Developed in MATLAB R2011b(7.13)                                 %
%                                                                   %
%  Author and programmer: Seyedali Mirjalili                        %
%                                                                   %
%         e-Mail: ali.mirjalili@gmail.com                           %
%                 seyedali.mirjalili@griffithuni.edu.au             %
%                                                                   %
%       Homepage: http://www.alimirjalili.com                       %
%                                                                   %
%   Main paper: S. Mirjalili, S. M. Mirjalili, A. Lewis             %
%               Grey Wolf Optimizer, Advances in Engineering        %
%               Software , in press,                                %
%               DOI: 10.1016/j.advengsoft.2013.12.007               %
%                                                                   %
%___________________________________________________________________%
% Grey Wolf Optimizer
function[Alpha_score,Alpha_pos,Convergence_curve]=GWO(SearchAgents_no,Max_iter,lb,ub,dim,fobj)
% initialize alpha, beta, and delta_pos
Alpha_pos=zeros(1,dim);
Alpha_score=inf; %change this to -inf for maximization problems
Beta_pos=zeros(1,dim);
Beta_score=inf; %change this to -inf for maximization problems
Delta_pos=zeros(1,dim);
Delta_score=inf; %change this to -inf for maximization problems
%Initialize the positions of search agents
Positions=initialization(SearchAgents_no,dim,ub,lb);
Convergence_curve=zeros(1,Max_iter);
l=0;% Loop counter
% Main loop
while l<Max_iter
    for i=1:size(Positions,1)  
        
       % Return back the search agents that go beyond the boundaries of the search space
        Flag4ub=Positions(i,:)>ub;
        Flag4lb=Positions(i,:)<lb;
        Positions(i,:)=(Positions(i,:).*(~(Flag4ub+Flag4lb)))+ub.*Flag4ub+lb.*Flag4lb;               
        
        % Calculate objective function for each search agent
        fitness=fobj(Positions(i,:));
        
        % Update Alpha, Beta, and Delta
        if fitness<Alpha_score 
            Alpha_score=fitness; % Update alpha
            Alpha_pos=Positions(i,:);
        end
        
        if fitness>Alpha_score && fitness<Beta_score 
            Beta_score=fitness; % Update beta
            Beta_pos=Positions(i,:);
        end
        
        if fitness>Alpha_score && fitness>Beta_score && fitness<Delta_score 
            Delta_score=fitness; % Update delta
            Delta_pos=Positions(i,:);
        end
    end
    
    
    a=2-l*((2)/Max_iter); % a decreases linearly fron 2 to 0
    
    % Update the Position of search agents including omegas
    for i=1:size(Positions,1)
        for j=1:size(Positions,2)     
                       
            r1=rand(); % r1 is a random number in [0,1]
            r2=rand(); % r2 is a random number in [0,1]
            
            A1=2*a*r1-a; % Equation (3.3)
            C1=2*r2; % Equation (3.4)
            
            D_alpha=abs(C1*Alpha_pos(j)-Positions(i,j)); % Equation (3.5)-part 1
            X1=Alpha_pos(j)-A1*D_alpha; % Equation (3.6)-part 1
                       
            r1=rand();
            r2=rand();
            
            A2=2*a*r1-a; % Equation (3.3)
            C2=2*r2; % Equation (3.4)
            
            D_beta=abs(C2*Beta_pos(j)-Positions(i,j)); % Equation (3.5)-part 2
            X2=Beta_pos(j)-A2*D_beta; % Equation (3.6)-part 2       
            
            r1=rand();
            r2=rand(); 
            
            A3=2*a*r1-a; % Equation (3.3)
            C3=2*r2; % Equation (3.4)
            
            D_delta=abs(C3*Delta_pos(j)-Positions(i,j)); % Equation (3.5)-part 3
            X3=Delta_pos(j)-A3*D_delta; % Equation (3.5)-part 3             
            
            Positions(i,j)=(X1+X2+X3)/3;% Equation (3.7)
            
        end
    end
    l=l+1;    
    Convergence_curve(l)=Alpha_score;
end

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Answer 1

Walter Roberson 2023-3-13

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1928090-this-two-code-are-connected-to-each-other-when-i-run-the-first-code-it-gives-me-error-says-error-us#answer_1192300

在 MATLAB Online 中打开

        [t_GWO(i),Nf_GWO(i),outcome_GWO(i),best_GWO(i,:),GWO_conv(i,:)]=GWO(N,T,lb,ub,dim,fitfun);
       %        1         2              3             4             5
       

That code requests 5 outputs from the GWO call.

       function[Alpha_score,Alpha_pos,Convergence_curve]=GWO(SearchAgents_no,Max_iter,lb,ub,dim,fobj)

That GWO function can only return 3 outputs. The only one of the outputs that appears to match the outputs you expect is the convergence, which is the third output from that GWO and the 5th output that you expect.

That GWO function does not match the way you expect to be able to call GWO.

I searched for a GWO that returns at least 5 outputs, but I was not able to find such a function anywhere -- I was also not able to find any place that called GWO expecting more than 3 outputs.