Evolving Flexible Beta Basis Function Neural Tree for Nonlinear Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F13%3A86089371" target="_blank" >RIV/61989100:27740/13:86089371 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IJCNN.2013.6706992" target="_blank" >http://dx.doi.org/10.1109/IJCNN.2013.6706992</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2013.6706992" target="_blank" >10.1109/IJCNN.2013.6706992</a>

Result language
angličtina
Original language name
Evolving Flexible Beta Basis Function Neural Tree for Nonlinear Systems
Original language description
In this paper, a new evolving artificial neural network using evolutionary computation is introduced. Based on the pre-defined Beta operator sets, this model called Flexible Beta Basis Function Neural Tree (FBBFNT), can be created and learned. The structure is developed using the Extended Immune Programming (EIP). The Beta parameters and connected weights are optimized using the Hybrid Bacterial Foraging Optimization algorithm. The performance of the proposed method is evaluated for nonlinear systems and compared with those of related methods.
Czech name
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Czech description
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the International Joint Conference on Neural Networks 2013
ISBN
978-1-4673-6129-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
New York
Event location
Dallas
Event date
Aug 4, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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