Training product unit networks using cooperative particle swarm optimisers

The cooperative particle swarm optimiser (CPSO) is a variant of the particle swarm optimiser (PSO) that splits the problem vector, for example a neural network weight vector, across several swarms. The paper investigates the influence that the number of swarms used (also called the split factor) has on the training performance of a product unit neural network. Results are presented, comparing the training performance of the two algorithms, PSO and CPSO, as applied to the task of training the weight vector of a product unit neural network