The basic and improved algorithms of PSO are focused on how
to search effectively the optimalsolution in the solution space by using one
of the particle swarm. However, the particles are always chasing the global
optimal point and such points are currently found on their way of search, rapidly
leading their speed down to zero and hence being restrained in the local minimum.
Consequently, there are the convergence or early maturity of particles. The
improved PSO is based on the enlightenment of Back-Propagation (BP) neural network
while the improvement is similar to the smooth weight through low-pass filter.
The test of classical functions show that the PSO provides a promotion in the
convergence precision and make better a certain extent in the calculation velocity.