Generation and simplification of Artificial Neural Networks by means of Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Rivero20103200,
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author = "Daniel Rivero and Julian Dorado and Juan Rabunal and
Alejandro Pazos",
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title = "Generation and simplification of Artificial Neural
Networks by means of Genetic Programming",
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journal = "Neurocomputing",
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year = "2010",
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volume = "73",
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number = "16-18",
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pages = "3200--3223",
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month = oct,
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note = "10th Brazilian Symposium on Neural Networks
(SBRN2008)",
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keywords = "genetic algorithms, genetic programming, Artificial
Neural Networks, ANN, Evolutionary computation",
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ISSN = "0925-2312",
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broken = "http://www.sciencedirect.com/science/article/B6V10-50GJ2JN-1/2/e32f0849c445d8250dfc0255ef5a27c5",
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DOI = "doi:10.1016/j.neucom.2010.05.010",
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size = "24 pages",
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abstract = "The development of Artificial Neural Networks (ANNs)
is traditionally a slow process in which human experts
are needed to experiment on different architectural
procedures until they find the one that presents the
correct results that solve a specific problem. This
work describes a new technique that uses Genetic
Programming (GP) in order to automatically develop
simple ANNs, with a low number of neurons and
connections. Experiments have been carried out in order
to measure the behaviour of the system and also to
compare the results obtained using other ANN generation
and training methods with evolutionary computation (EC)
tools. The obtained results are, in the worst case, at
least comparable to existing techniques and, in many
cases, substantially better. As explained herein, the
system has other important features such as variable
discrimination, which provides new information on the
problems to be solved.",
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notes = "Department of Information and Communication
Technologies, University of A Coruna, A Coruna, Spain",
- }
Genetic Programming entries for
Daniel Rivero Cebrian
Julian Dorado
Juan Ramon Rabunal Dopico
Alejandro Pazos Sierra
Citations