Detail publikace

Optimization of multilayer perceptron training parameters using artificial bee colony and genetic algorithm

KARTCI, A.

Originální název

Optimization of multilayer perceptron training parameters using artificial bee colony and genetic algorithm

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper, the momentum coefficient, learning rate, and the number of hidden neurons where the multilayer perceptron works best, are determined. The network and optimization algorithms are written in MATLAB, which was also successfully used to carry out results. To obtain the results, IRIS, mammographic_mass, and new_thyroid data sets have been used. Obtained results show that the determining effect on the neural learning process of parameters (momentum coefficient, learning rate, number of hidden neurons) are compatible with other approaches available in the literature. Both genetic algorithm (GA) and artificial bee colony (ABC) algorithm were successful on finding the values to get high performance as well as effect on performance of the population number.

Klíčová slova

Multilayer perceptron, artificial bee colony algorithm, genetic algorithm, training parameters optimization

Autoři

KARTCI, A.

Rok RIV

2015

Vydáno

23. 4. 2015

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo

Brno

ISBN

978-80-214-5148-3

Kniha

Proceedings of the 21st Conference STUDENT EEICT 2015

Strany od

338

Strany do

340

Strany počet

3

BibTex

@inproceedings{BUT117521,
  author="Aslihan {Kartci}",
  title="Optimization of multilayer perceptron training parameters using artificial bee colony and genetic algorithm",
  booktitle="Proceedings of the 21st Conference STUDENT EEICT 2015",
  year="2015",
  pages="338--340",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5148-3"
}