Sir I want to complete my matlab code which title is energy efficiency unequal clustering algorithm with multilevel fuzzy logic and want to given result which is shown in the pictureplease help me.....

clear; %Field Dimensions - x and y maximum (in meters)/ Tarife Size mohite shabake(m) xm=100; ym=100; p=1; %x and y Coordinates of the Sink / sink.x=0.5*xm; sink.y=0.5*ym; %Number of Nodes in the field / Tedade Node haye shabake n=100; number_of_ch=0.1*n; %Optimal Election Probability of a node to become cluster head/ Ehtemale Entekhab Node be onvane Cluster Head %p=0.1; %Energy Model (all values in Joules)/ Energy ha bar hasbe Joule %Initial Energy / Energy Avaliye Eo=0.5; %maximum number of rounds %rmax=input('enter the number of iterations you want to run : '); rmax=3000;

figure(1); for i=1:1:n S(i).xd=rand(1,1)*xm; XR(i)=S(i).xd; S(i).yd=rand(1,1)*ym; YR(i)=S(i).yd; S(i).G=0;

    S(i).E=Eo;

    % Calculation of distance from sink node to normal node %
     D(i)=sqrt(((S(i).xd-50)^2)+ ((S(i).yd-50)^2)); 

     R(i)=(D(i)+Eo*150)*3;

    %initially there are no cluster heads only nodes/ Dar ebteda hich Cluster Head i mojud nist
    S(i).type='N';
    S(i).e=Eo

    %temp_rnd0=i;
    %Random Election of Normal Nodes/ Entekhabe Tasadofi Node ha 
        plot(S(i).xd,S(i).yd,'o',...
            'markerFace','b');
        hold on;

end S(n+1).xd=sink.x; S(n+1).yd=sink.y; plot(sink.x,sink.y,'o', ... 'markerSize',15,'markerFace','r'); hold on;

%Eelec=Etx=Erx ETX=50*0.000000001; ERX=50*0.000000001; %Transmit Amplifier types Efs=10*0.000000000001; Emp=0.0013*0.000000000001; %Data Aggregation Energy EDA=5*0.000000001;

%Computation of do do=sqrt(Efs/Emp); S3=S; totalclust=10; %First Iteration %counter for CHs LcountCHs=0; %counter for CHs per round LrcountCHs=0; Lcluster=1;

%LcountCHs; LrcountCHs=LrcountCHs+LcountCHs; Lflag_first_dead=0;

figure(3) for r=1:rmax r hold off;

clust = randperm(n,totalclust); for i=1:totalclust

% clust=randi(n,1); S3(clust(i)).type='C'; cluster(i)=clust(i); end

 for i=1:totalclust
     plot(S3(cluster(i)).xd,S3(cluster(i)).yd,'*-g');
     hold on;
 end
  plot(S3(n+1).xd,S3(n+1).yd,'o', 'MarkerSize', 12, 'MarkerFaceColor', 'r');  
  hold on;

 for i=1:totalclust
     clster_count(i)=0;
 end
 for i=1:n
%      if(S3(i).type=='N')
%          min_dis=sqrt( (S3(i).xd-S3(n+1).xd)^2 + (S3(i).yd-S3(n+1).yd)^2 );
         min_dis=999999;
         k=n+1;
         k1=totalclust+1;
        for j=1:totalclust
             min_dis2=sqrt( (S3(i).xd-S3(cluster(j)).xd)^2 + (S3(i).yd-S3(cluster(j)).yd)^2 );
             if(min_dis2<min_dis)
                 min_dis=min_dis2;

                 k=cluster(j);
                 k1=j;
             end

        end
%        node_number(k1,i)=cluster(j); 
      S3(i).clustnum= k1;
      S3(i).clustnode= k;
      line([S3(i).xd, S3(k).xd], [S3(i).yd, S3(k).yd], 'Color', 'b', 'LineWidth', 0.5);
       hold on;
      clster_count(k1)=clster_count(k1)+1;
%             line([S3(i).xd, S3(k).xd], [S3(i).yd, S3(k).yd], 'Color', 'b', 'LineWidth', 0.5);
%        hold on;

% end end for j=1:totalclust total_node(j)=0; incre(j)=1; end for i=1:n % if (S3(i).type=='N') for j=1:totalclust if (S3(i).clustnum==j) total_node(j)=total_node(j)+1; node_no(j,incre(j))=i; res_energy(j,incre(j))=S3(i).E; incre(j)=incre(j)+1; end end % end end

     for i=1:totalclust
         for j=1:total_node(i)
             dist_bs(i,j)=sqrt( (S3(node_no(i,j)).xd-S3(n+1).xd)^2 + (S3(node_no(i,j)).yd-S3(n+1).yd)^2 );
         end
         j=j+1;
         dist_bs(i,j)=sqrt( (S3(cluster(i)).xd-S3(n+1).xd)^2 + (S3(cluster(i)).yd-S3(n+1).yd)^2 );
     end
      for i=1:totalclust
         for j=1:total_node(i)
             max_dist(i,j)=0;
             total_dist(i,j)=0;
            for k=1:total_node(i)
                 max_dis2=sqrt( (S3(node_no(i,j)).xd-S3(node_no(i,k)).xd)^2 + (S3(node_no(i,j)).yd-S3(node_no(i,k)).yd)^2 );
             total_dist(i,j)=total_dist(i,j)+ max_dis2;
              if(max_dis2>max_dist(i,j))
                 max_dist(i,j)=max_dis2;
              end
            end
         end
      end
        for i=1:totalclust
         for j=1:total_node(i)
               avg_dist(i,j)=total_dist(i,j)/total_node(i);
                distance1=sqrt((S3(node_no(i,j)).xd-S3(n+1).xd)^2 + (S3(node_no(i,j)).yd-S3(n+1).yd)^2 );
                if(distance1>do)
                min_energy(i,j)=4000* total_node(i) * ERX+ 4000* Emp* ETX * distance1*distance1*distance1*distance1;
                else
                     min_energy(i,j)=4000* total_node(i) * ERX+ 4000* Emp* ETX *distance1*distance1;
                end
         end
        end
       for i=1:totalclust
         for j=1:total_node(i)
             delay(i,j)=res_energy(i,j);
         end
       end
     alpha=0.33;
     beta=0.33;
     gama=0.33;
     for i=1:totalclust
         for j=1:total_node(i)
             fitness(i,j)=delay(i,j);
         end
     end
      [B I]=sort(fitness,2,'descend');

      for i=1:totalclust
     selected_ch(i)=node_no(i,I(i,total_node(i)));
     if (selected_ch(i)==0)
         selected_ch(i)=node_no(i,I(i,total_node(i))-1);
     end
     if (selected_ch(i)==0)
         selected_ch(i)=node_no(i,I(i,total_node(i))-2);
     end
      end

     for i=1:n
         S3(i).type='N';
     end

     for j=1:n
         for i=1:totalclust
         if (j==selected_ch(i))
         S3(i).type='C';
         end
         end
     end

     % Same for all algorithms
     for i=1:n
         if (S3(i).type=='N')
             for j=1:totalclust
                 if (S3(i).clustnum==j)
              min_dis=sqrt( (S3(i).xd-S3(selected_ch(j)).xd)^2 + (S3(i).yd-S3(selected_ch(j)).yd)^2 );
              if (min_dis>do)
                S3(i).E=S3(i).E - ( ETX *(4000) + Emp*4000*( min_dis * min_dis * min_dis * min_dis)); 
            end
            if (min_dis<=do)
                S3(i).E=S3(i).E - ( ETX *(4000) + Efs*4000*( min_dis * min_dis)); 
            end
                 end
             end
         else
            Ldistance=sqrt( (S3(i).xd-S3(n+1).xd)^2 + (S3(i).yd-S3(n+1).yd)^2 );
              if (Ldistance>do)
                S3(i).E=S3(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( Ldistance*Ldistance*Ldistance*Ldistance )); 

            %S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( Ldistance*Ldistance*Ldistance*Ldistance )); 
            end
            if (Ldistance<=do)
                S3(i).E=S3(i).E - ( (ETX+EDA)*(4000)  + Efs*4000*( Ldistance * Ldistance )); 
            %S2(i).E=S2(i).E- ( (ETX+EDA)*(4000)  + Efs*4000*( Ldistance * Ldistance )); 
            end
         end
     end

     % Same for all algorithms
    for i=1:n
         if(S3(i).E>0)
         Eres(r,i)=S3(i).E;
         else
             Eres(r,i)=0;
             S3(i).E=0;
         end
    end

      deadnode=0;
     %figure(4);
     %Same for all algoriths.
     for i=1:n
         dead(i)=0;
        if(S3(i).E<=0)
            dead(i)=dead(i)+1;
            deadnode=deadnode+1;
            %S3(i).type='D'
            %plot(S(i).xd,p,'o',...
             %   'markerFace','b');

            % hold on;
            % p=p+1;
        end
     end
     d(r)=deadnode;

end

 % no of nodes remaining after each rounds
 for r=1:rmax
     figure(4);
     plot(p,n-d(r),'o',...
      'markerSize',5,'markerFace','g');
     hold on;
     p=p+1;
 end

[Avinash Chaudhary]

[Avinash Chaudhary]

Want that results when I'm run the code please help me

[Walter Roberson]

please format as code.

Please ask a more specific question. Are you getting an error message? can you direct us to a particular place in the code where you are not getting the results you expect? What results are you expecting for the section and what are you getting instead?

People are not going to read through hundreds of lines of code and research the paper you are using and dig through to find something in the code that might be in some small way different than the diagram. You need to focus attention, or people are just going to move on to a posting that asks better questions.