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IJON
2006

Evolutionary system for automatically constructing and adapting radial basis function networks

10 years 1 months ago
Evolutionary system for automatically constructing and adapting radial basis function networks
This article presents a new system for automatically constructing and training radial basis function networks based on original evolutionary computing methods. This system, called Genetic Algorithm Radial Basis Function Networks (GARBFN), is based on two cooperating genetic algorithms. The first algorithm uses a new binary coding, called basic architecture coding, to get the neural architecture that best solves the problem. The second, which uses real coding, takes its inspiration from mathematical morphology theory and trains the architectures output by the binary genetic algorithm. This system has been applied to a laboratory problem and to breast cancer diagnosis. The results of these evaluations show that the overall performance of GARBFN is better than other related approaches, whether or not they are based on evolutionary techniques. r 2005 Elsevier B.V. All rights reserved.
Daniel Manrique, Juan Rios, Alfonso Rodrígu
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where IJON
Authors Daniel Manrique, Juan Rios, Alfonso Rodríguez-Patón
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