Multi-agent evolutionary design of Flexible Beta Basis Function Neural Tree
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092829" target="_blank" >RIV/61989100:27240/14:86092829 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86092829
Result on the web
<a href="http://dx.doi.org/10.1109/IJCNN.2014.6889726" target="_blank" >http://dx.doi.org/10.1109/IJCNN.2014.6889726</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2014.6889726" target="_blank" >10.1109/IJCNN.2014.6889726</a>
Alternative languages
Result language
angličtina
Original language name
Multi-agent evolutionary design of Flexible Beta Basis Function Neural Tree
Original language description
Multi-Agent System (MAS) is a very active field that ensures global coherence between agents' interactions in a distributed way and implicit global control. Under the awareness of its power, the application of MAS was no more limited to very specific problems, but to almost application area: optimization, neural network, robotics, fuzzy system, etc. In the other side, a complex system of Artificial Neural Network called Flexible Beta Basis Function Neural Tree (FBBFNT) has reached a great level in the prediction search domain. In the purpose of enlarging the application of the algorithm to complex applications of the real problems, a new architecture of MAS was designed and applied to the FBBFNT process. This new multi-agent system based on communications and negotiations allowed the resolution of more complex prediction problems and the acceleration of the global convergence speed. 2014 IEEE.
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
<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)
Others
Publication year
2014
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
ISBN
978-1-4799-1484-5
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1265-1271
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
New York
Event location
Beijing
Event date
Jul 6, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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