Partially-Connected Artificial Neural Networks Developed by Grammatical Evolution for Pattern Recognition Problems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InCollection{series/sci/Quiroz-RamirezEODSSCEO18,
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author = "Olga Quiroz-Ramirez and Andres Espinal and
Manuel Ornelas-Rodriguez and Alfonso Rojas Dominguez and
Daniela Sanchez and Hector Jose Puga Soberanes and
Martin Carpio and Luis Ernesto Mancilla Espinoza and
Janet Ortiz-Lopez",
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title = "Partially-Connected Artificial Neural Networks
Developed by Grammatical Evolution for Pattern
Recognition Problems",
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booktitle = "Fuzzy Logic Augmentation of Neural and Optimization
Algorithms: Theoretical Aspects and Real Applications",
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publisher = "Springer",
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year = "2018",
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editor = "Oscar Castillo and Patricia Melin and
Janusz Kacprzyk",
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volume = "749",
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series = "Studies in Computational Intelligence",
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pages = "99--112",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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bibdate = "2018-01-16",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/series/sci/sci749.html#Quiroz-RamirezEODSSCEO1",
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isbn13 = "978-3-319-71007-5",
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DOI = "doi:10.1007/978-3-319-71008-2_9",
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abstract = "Evolutionary Artificial Neural Networks (EANNs) are a
special case of Artificial Neural Networks (ANNs) for
which Evolutionary Algorithms (EAs) are used to modify
or create them. EANNs adapt their defining components
ad hoc for solving a particular problem with little or
no intervention of human expert. Grammatical Evolution
(GE) is an EA that has been used to indirectly develop
ANNs, among other design problems. This is achieved by
means of three elements: a Context-Free Grammar (CFG)
which includes the ANNs defining components, a search
engine that drives the search process and a mapping
process. The last component is a heuristic for
transforming each GE's individual from its genotypic
form into its phenotypic form (a functional ANN).
Several heuristics have been proposed as mapping
processes in the literature; each of them may transform
a specific individual's genotypic form into a very
different phenotypic form. In this paper,
partially-connected ANNs are automatically developed by
means of GE. A CFG is proposed to define the
topologies, a Genetic Algorithm (GA) is the search
engine and three mapping processes are tested for this
task; six well-known pattern recognition benchmarks are
used to statistically compare them. The aim of this
work for using and comparing different mapping process
is to analyse them for setting the basis of a generic
framework to automatically create ANNs.",
- }
Genetic Programming entries for
Olga Quiroz-Ramirez
Andres Espinal Jimenez
Manuel Ornelas-Rodriguez
Alfonso Rojas-Dominguez
Daniela Sanchez
Hector J Puga
Juan Martin Carpio-Valadez
Luis Ernesto Mancilla Espinoza
Janet Ortiz-Lopez
Citations