How to use PSO (Particle swarm optimization) to optimize objective function containing two terms one of them kmeans clustering?
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Hi
I used PSO before to optimize an objective function.Now I have an objective(fitness) function containing two terms; one of them described by k-means clustering ..Euclidean distance?
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Walter Roberson
2019-1-19
0 个投票
You have to pass a function handle as the objective function, but it does not have to be an anonymous function. You can pass the handle to a function that does extensive computation based on the inputs. The only requirement is that the output has to be a scalar.
If you are trying to minimize two distinct things simultaneously then you either need to decide their relative weighting to combine them into a scalar, or else you need to use gamultiobj() to find pareto fronts.
14 个评论
M.Shaarawy
2019-1-19
Walter Roberson
2019-1-19
I do not understand that image?
M.Shaarawy
2019-1-19
M.Shaarawy
2019-1-19
Walter Roberson
2019-1-20
This is what your image looks like at my end:
No phi, no first or second term.
M.Shaarawy
2019-1-20
Walter Roberson
2019-1-20
that looks like weighted Euclidean not plain Euclidean .
M.Shaarawy
2019-1-20
M.Shaarawy
2019-1-20
I have the Wi matrix so how to implement this weighted Euclidean distance?
To get results like these in the images
M.Shaarawy
2019-1-20
Walter Roberson
2019-1-21
编辑：Walter Roberson
2019-1-21
Use a nested for loop if you need to.
total = 0;
for j = 1 : K
for i = 1 : N2
total = total + sum(sum((W(i) * bsxfun(@minus, V(mu(j)).^i, mu(j)))).^2));
end
end
Here I assume that V_(mu_j) must indicate a function named V that is being passed a scalar mu(j) and is returning a vector or array -- if V_mu_j is a scalar then it makes less sense to talk about a Euclidean distance. If mu(j) represents a vector or array, or Wi is a vector or array, the code might need to be revised. If we had information about the relative dimensions we might potentially be able to write much more compact code.
M.Shaarawy
2019-1-21
Wi : is vector
See the attached for more 
information
information
M.Shaarawy
2019-1-21
M.Shaarawy
2019-1-22
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