neural network trained using partical swarm optimization
6 views (last 30 days)
Show older comments
Hello
in order to resolve some constraints optimization problem, i use neural network trained by pso algorithm.
to this end i try to simulate the matlab code proposed in:
however, it generate the following error:
Error using network/subsasgn>network_subsasgn (line 551)
net.IW{1,1} must be a 10-by-3 matrix.
Error in network/subsasgn (line 11)
net = network_subsasgn(net,subscripts,v,netname);
Error in myfunc (line 18)
net.iw{1,1}=xi; % net.inputWeights{1,1}
Error in rnn_pso>@(x)myfunc(x,n,m,o,net,inputs,targets)
Error in rnn_pso (line 37)
f0(i,1)=fun(x0(i,:));
the size of used data: 150x7 input, 150x3 target.
how can i overcome it?
Did you already test this code? othwhise, i can post the code for do it.
4 Comments
BERGHOUT Tarek
on 3 Feb 2019
i used the same code but it works perfectly for any dataset that i used; just check this parameters number of neurons in the hidden layer; nulmber of inputs ; number of outputs ;
ERJEW AYEL D
on 28 Oct 2021
Dear,
Could you please tell me how to adjust the output neurons! for example, I have 8 output variables so that the output layer contains 8 neurons!
Thank you in advance!
Answers (1)
Greg Heath
on 29 Jun 2017
You should have
[ I N ] = size(input) = [ 7 150]
[ O N ] = size(target) = [ 3 150 ]
Hope this helps.
Thank you for formally accepting my answer
Greg
0 Comments
See Also
Categories
Find more on Sequence and Numeric Feature Data Workflows in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!