Evolutionary Design of Application Tailored Neural Networks
نویسندگان
چکیده
| First, an evolutionary algorithm for designing a single hidden layer feedfor-ward neural networks is proposed. The algorithm constructs a problem tailored neu-ral network by incremental introduction of new hidden units. Each new hidden unit is added to the network by linear partitioning of the hidden-layer representation through a genetic search. Second, a two stage algorithm speed-up is achieved through: (1) distributed genetic search for hidden layer units construction along with the appropriate input to hidden layer weights; and (2) the dynamic pocket algorithm for learning the hidden to output layer weights. Finally, promising experimental results are presented on fast construction of small networks having good generalization property.
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