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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU115799" target="_blank" >RIV/00216305:26220/15:PU115799 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Optimization of multilayer perceptron training parameters using artificial bee colony and genetic algorithm
Original language description
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 carryout 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.
Czech name
—
Czech description
—

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 21st Conference STUDENT EEICT 2015
ISBN
978-80-214-5148-3
ISSN
—
e-ISSN
—
Number of pages
3
Pages from-to
338-340
Publisher name
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Place of publication
Brno
Event location
Brno
Event date
Apr 23, 2015
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
—

Similar results(10)