Implementation of neural network in particle swarm optimization (PSO) techniques

Abstract

this paper describes different techniques of particle swam optimization (PSO), implementing feed-forward architecture in neural network. The algorithms for different types of optimization techniques are developed. These algorithms leads to optimum search solution to a given problem. The new position of the particle is calculated considering the best technique for PSO.