A review of genetic algorithms applied to training radial basis function networks

Authors:
C. Harpham;W. Dawson;R. Brown
Affiliations:
King’s College London, Department of Geography, Strand, WC2R 2LS, London, UK;Loughborough University, Department of Computer Science, Strand, LE11 3TU, London, Leicestershire, UK;University of Central Lancashire, Department of Computing, Strand, PR1 2HE, Preston, Lancashire, UK
Venue:
Neural Computing and Applications
Year:
2004

Citing 0
Cited 19

EvRBF: evolving RBF neural networks for classification problems

AIC'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Informatics and Communications - Volume 7
Time series prediction using evolving radial basis function networks with new encoding scheme

Neurocomputing
Automatic Neural Net Design by Means of a Symbiotic Co-evolutionary Algorithm

HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Finding optimal model parameters by deterministic and annealed focused grid search

Neurocomputing
A Preliminar Analysis of CO2RBFN in Imbalanced Problems

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
CO$^2$RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market

International Journal of Hybrid Intelligent Systems - Hybrid Fuzzy Models
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets

Pattern Recognition Letters
Intelligent systems in long-term forecasting of the extra-virgin olive oil price in the Spanish market

IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods

Applied Intelligence
Multi-label testing for CO2RBFN: a first approach to the problem transformation methodology for multi-label classification

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
An optimizing BP neural network algorithm based on genetic algorithm

Artificial Intelligence Review
Radial basis function neural network based on PSO with mutation operation to solve function approximation problem

ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Evolutionary computation and its applications in neural and fuzzy systems

Applied Computational Intelligence and Soft Computing
Hierarchical multi-dimensional differential evolution for the design of beta basis function neural network

Neurocomputing
Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

Expert Systems with Applications: An International Journal
Evolutionary artificial neural networks: a review

Artificial Intelligence Review
Alternative OVA proposals for cooperative competitive RBFN design in classification tasks

IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects

Cybernetics and Systems Analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

The problems associated with training feedforward artificial neural networks (ANNs) such as the multilayer perceptron (MLP) network and radial basis function (RBF) network have been well documented. The solutions to these problems have inspired a considerable amount of research, one particular area being the application of evolutionary search algorithms such as the genetic algorithm (GA). To date, the vast majority of GA solutions have been aimed at the MLP network. This paper begins with a brief overview of feedforward ANNs and GAs followed by a review of the current state of research in applying evolutionary techniques to training RBF networks.