Publication detail

Genetic Algorithm and Neural Network

ŠŤASTNÝ, J. ŠKORPIL, V.

Original Title

Genetic Algorithm and Neural Network

Type

journal article in Web of Science

Language

English

Original Abstract

This paper describes application of Genetic algorithm (GA) for design of network configuration and for learning of neural network. Design of network configuration is the first area for GA exercise in relation to neural network. The number of neurons in network and placement to the layers has big influence over effectivity of whole system. If we are able to formulate quality classification of designed network from standpoint of topology, we can use GA for design of suitable network configuration. The second area (learning of neural network) consists in using of advantages of GA toward learning of neural networks. In this case GA looks for acceptable setting of network weights so, to make specified transformation - it practices minimalization of its mistake function. The Genetic algorithm is considered to be a stochastic heuristic (or meta-heuristic) method. Genetic algorithms are inspired by adaptive and evolutionary mechanisms of live organisms. The best use of Genetic algorithm can be found in solving multidimensional optimisation problems, for which analytical solutions are unknown (or extremely complex) and efficient numerical methods are also not known.

Keywords

Genetic algorithm, fitness function, neural network, back-propagation method.

Authors

ŠŤASTNÝ, J.; ŠKORPIL, V.

RIV year

2007

Released

24. 8. 2007

Publisher

WSEAS

Location

Athény

ISBN

1790-5117

Periodical

WSEAS Applied Informatics & Communications

Year of study

2007

Number

3

State

Hellenic Republic

Pages from

347

Pages to

351

Pages count

5

BibTex

@article{BUT44959,
  author="Jiří {Šťastný} and Vladislav {Škorpil}",
  title="Genetic Algorithm and Neural Network",
  journal="WSEAS Applied Informatics & Communications",
  year="2007",
  volume="2007",
  number="3",
  pages="347--351",
  issn="1790-5117"
}