help in Kmeans modified clustring
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Dear experiences,
I am new in Matlab programmation. So I used Kmeans for found the barycenter of UAV with it set of users connected.
My problem I didn't know if this is code is correct or not.
I calculate the Matrix A end Eta in another Function which called "Matching". I use the HPPP and Monte-Carlo simulation to initialisation of the position of users and UAVs.
So in this code, I update the matrix of Association A if the user is associate with drone (A(i,j)==1) then I calculate the position of drone.
Can you help me pleaase and How I show the cluster
function [cluster,center] = Placement(H,B)
global xu yu
%initialisation
e=length(B);
k = e ;%cardinal de B^A
numP = 3 ; %nombre des UAVs
center = zeros(numP, 2);
Xmax=1000; %X entre 0 et Xmax
Ymax=1000; %Y entre 0 et Ymax
y=3;
U=5;
%% Choose k data points as initial centroids
xP = Xmax * rand(1,numP); % position des drones aleatoires
yP = Ymax * rand(1,numP); % position des drones aleatoires
UAVspoints = [xP; yP]; %coordonées des drones
%% Repeat until number of iteration is reached or barycenter is inchangeabale
% init cluster array
cluster=zeros(5,3); % to execute rapidly I supposed we have 5 users and 3 drones
max_iteration=5; % I chose littre number to obtain the result rapedaly
startingTime = tic;
% debut de programme Kmeans
res=0;
iteration=1;
while iteration < max_iteration || res~=1 % boucle pour la convergence de Kmean
fprintf('iteration = %d\n', iteration);
for j=1:e-1
[A,Eta]=Matching(H,B,xP(j),yP(j)); %update de Eta et Association par l'algorithme 1(Matching)
fprintf('j = %d\n', j);
c=0;
c=xP(j); %initialisation %% I take every point what I defined in UAVspoints
b=yP(j);
for i=1:U-1
if A(i,j)==1 && A(i+1,j)==1 % si un utilisateur est associer a une drone alor A(ij)=1
c(j) =i; %je veux obtenir les indices des utilisateurs associés pour chaque drone
% debut de recherche de barycentre (il faut drones prendre sa position au barycentre des utilisateurs connecté a lui )
xP(j)=(xP(j)+xu(i))/length(c);
yP(j)=(yP(j)+yu(i))/length(c);
xP(j+1)=(xP(j+1)+xu(i+1))/length(c);
yP(j+1)=(yP(j+1)+yu(i+1))/length(c);
end
% cette etape pour verifier que la drone est trouvé sa barycentre donc ses coordonnées ne changent pas
%(d'ou sortie de la boucle While)
if xP(j)~= yP(j+1) && yP(j)~=yP(j+1)
res=0;
else res =1;
end
end
center(k, :)=[xP(j); yP(j)];
L=length(c);
cluster(1:L,j) = c';
end
iteration = iteration + 1;
end
end
댓글 수: 5
Image Analyst
2020년 6월 28일
I'm sure people who try to solve/run this for you will want H, B, and the function Matching() that you forgot to attach.
Meriem Ben Kalia
2020년 6월 28일
Image Analyst
2020년 6월 28일
Make it easy for people to help you, not hard. Are you really expecting people to write their own Matching() function? I don't think anyone will do that.
Image Analyst
2020년 6월 28일
편집: Image Analyst
2020년 6월 28일
You have a j loop inside another j loop, and the capitalization of center is not consistent -- Center is different than center. Plus you don't need semicolons after an end statement. I fixed those problems and attached it in case anyone else wants to give it a try. How long is it supposed to take? I ran it for several minutes and it never finished. I got up to iteration 12.
Meriem Ben Kalia
2020년 6월 28일
답변 (1개)
Image Analyst
2020년 6월 28일
0 개 추천
Hopefully this attached m-file will work for you. I have no idea what it does, and it take a long time per iteration, but at least it runs.
댓글 수: 2
Meriem Ben Kalia
2020년 6월 28일
편집: Meriem Ben Kalia
2020년 6월 28일
Image Analyst
2020년 6월 29일
Well you wrote the program. I have no idea what it does, but since you do, go ahead and correct the remaining errors.
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