MATLAB: I want to optimize a neural network parameters by genetic algorithm and i get below code from matlab support, but the result is very poor even for a very simple function. how can i improve the result and is there any better code for the porpuse

Question

function mse_calc = mse_test(x, net, inputs, targets)
% 'x' contains the weights and biases vector
% in row vector form as passed to it by the
% genetic algorithm. This must be transposed
% when being set as the weights and biases
% vector for the network.
% To set the weights and biases vector to the
% one given as input
net = setwb(net, x');
% To evaluate the ouputs based on the given
% weights and biases vector
y = net(inputs);
% Calculating the mean squared error
mse_calc = sum(abs(y-targets)/length(y);
end
% INITIALIZE THE NEURAL NETWORK PROBLEM %
% inputs for the neural net
inputs = (-2:.01:2);
% targets for the neural net
targets = ((inputs).^2)-3;
% number of neurons
n = 4;
% create a neural network
net = feedforwardnet(n);
% configure the neural network for this dataset
net = configure(net, inputs, targets);
% create handle to the MSE_TEST function, that
% calculates MSE
h = @(x) mse_test(x, net, inputs, targets);
% Setting the Genetic Algorithms tolerance for
% minimum change in fitness function before
% terminating algorithm to 1e-8 and displaying
% each iteration's results.
ga_opts = gaoptimset('PopInitRange', [-1;1], 'TolFun', 1e-10,'display','iter');
ga_opts = gaoptimset(ga_opts, 'StallGenLimit', 100, 'FitnessLimit', 1e-5, 'Generations', 400);
% PLEASE NOTE: For a feed-forward network
% with n neurons, 3n+1 quantities are required
% in the weights and biases column vector.
% a. n for the input weights
% b. n for the input biases
% c. n for the output weights
% d. 1 for the output bias
% running the genetic algorithm with desired options
[x, err_ga] = ga(h, 3*n+1, ga_opts);
net = setwb(net, x');

Answer 1

http://www.mathworks.com/matlabcentral/newsreader/view_thread/344888#944621

If you can improve the code please let me know.

Greg