Comparing hybrid systems to design and optimize artificial neural networks

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{castillo:2004:eurogp,

• author = "Pedro A. Castillo and Maribel G. Arenas and J. J. Merelo and Gustavo Romero and Fatima Rateb and Alberto Prieto",
• title = "Comparing hybrid systems to design and optimize artificial neural networks",
• booktitle = "Genetic Programming 7th European Conference, EuroGP 2004, Proceedings",
• year = "2004",
• editor = "Maarten Keijzer and Una-May O'Reilly and Simon M. Lucas and Ernesto Costa and Terence Soule",
• volume = "3003",
• series = "LNCS",
• pages = "240--249",
• address = "Coimbra, Portugal",
• publisher_address = "Berlin",
• month = "5-7 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming: Poster",
• ISBN = "3-540-21346-5",
• DOI = "doi:10.1007/978-3-540-24650-3_22",
• abstract = "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.",
• notes = "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in conjunction with EvoCOP2004 and EvoWorkshops2004",

}

Genetic Programming entries for Pedro A Castillo Valdivieso Maribel Garcia Arenas Juan Julian Merelo Gustavo Romero Fatima Rateb Alberto Prieto Espinosa

Citations