neural-network,genetic-algorithm,encog,simulated-annealing,particle-swarm

It seems logical, however it will not work. With the default parameters of the RPROP, this sequence will not likely work. The reason why is that after your previous training the weights of the neural network will be near a local optimum. Because of the nearness to a local optimum...

algorithm,mathematical-optimization,particle-swarm

Your terminology is a bit off. Simple PSO is a search for a vector x that minimizes some scalar objective function E(x). It does this by creating many candidate vectors. Call them x_i. These are the "particles". They are initialized randomly in both position and rate of change, also called...

python,magic-methods,particle-swarm

You are treating a single particle() instance as a list here: val = val + (k[i])**2 - 10*cos(2*pi*k[i]) k is an instance of particle(), the [i] syntax translates to a __getitem__ call on that instance. You are passing in that instance here: gbest = new_swarm[0] gbestfit = functR(gbest) while elsewhere...