Designing Beta Basis Function Neural Network for Optimization Using Artificial Bee Colony (ABC)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084577" target="_blank" >RIV/61989100:27240/12:86084577 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Designing Beta Basis Function Neural Network for Optimization Using Artificial Bee Colony (ABC)
Original language description
This paper presents an application of swarm intelligence technique namely Artificial Bee Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN). The focus of this research is to investigate the new population meta-heuristicto optimize the Beta neural networks parameters. The proposed algorithm is used for the prediction of benchmark problems. Simulation examples are also given to compare the effectiveness of the model with the other known methods in the literature. Empirical results reveal that the proposed ABC-BBFNN have impressive generalization ability.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Joint Conference on Neural Networks 2012
ISBN
978-1-4673-1490-9
ISSN
1098-7576
e-ISSN
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Number of pages
7
Pages from-to
1-7
Publisher name
IEEE
Place of publication
New York
Event location
Brisbane
Event date
Jun 10, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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