Neural network construction and training using grammatical evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Tsoulos2008269,
-
author = "Ioannis Tsoulos and Dimitris Gavrilis and
Euripidis Glavas",
-
title = "Neural network construction and training using
grammatical evolution",
-
journal = "Neurocomputing",
-
volume = "72",
-
number = "1-3",
-
pages = "269--277",
-
year = "2008",
-
note = "Machine Learning for Signal Processing (MLSP 2006) /
Life System Modelling, Simulation, and Bio-inspired
Computing (LSMS 2007)",
-
ISSN = "0925-2312",
-
DOI = "doi:10.1016/j.neucom.2008.01.017",
-
URL = "http://www.sciencedirect.com/science/article/B6V10-4S1C894-3/2/9beaf5f426239399e63b31456dcbc52a",
-
keywords = "genetic algorithms, genetic programming, Grammatical
evolution, Neural network, Context-free grammar",
-
abstract = "The term neural network evolution usually refers to
network topology evolution leaving the network's
parameters to be trained using conventional algorithms.
In this paper we present a new method for neural
network evolution that evolves the network topology
along with the network parameters. The proposed method
uses grammatical evolution to encode both the network
and the parameters space. This allows for a better
description of the network using a formal grammar
allowing the network architect to shape the resulting
search space in order to meet each problem requirement.
The proposed method is compared with other three
methods for neural network training and is evaluated
using 9 known classification problems and 9 known
regression problems. In all 18 datasets, the proposed
method outperforms its competitors.",
- }
Genetic Programming entries for
Ioannis G Tsoulos
Dimitris Gavrilis
Euripidis Glavas
Citations