chaotic particle swarm optimization
A new particle swarm optimization (PSO) algorithm with has a chaotic neural network structure, is proposed. The structure is similar to the Hopfield neural network with transient chaos, and has an improved ability to search for globally optimal solution and does not suffer from problems of premature convergence. The presented PSO model is discrete-time discrete-state. The bifurcation diagram of a particle shows that it converges to a stable fixed point from a strange attractor, guaranteeing system convergence.
chaos particle swarm optimization neural network convergence