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Comparing hybrid systems to design and optimize artificial neural networks
Genetic Programming 7th European Conference, EuroGP 2004, Proceedings, том 3003 из LNCS, стр. 240--249. Coimbra, Portugal, Springer-Verlag, (5-7 April 2004)
Аннотация
We conduct a comparative study between hybrid methods
to optimise multi-layer perceptrons: a model that
optimises the architecture and initial weights of multi
layer perceptrons; a parallel approach to optimise the
architecture and initial weights of multilayer
perceptrons; a method that searches for the parameters
of the training algorithm, and an approach for
cooperative co-evolutionary optimisation of multi layer
perceptrons. Obtained results show that a
co-evolutionary model obtains similar or better results
than specialised approaches, needing much less training
epochs and thus using much less simulation time.
