Training Product Unit Networks using Cooperative Particle Swarm Optimisers
نویسنده
چکیده
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. This 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.
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