Hybrid Evolution of Heterogeneous Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A00145831" target="_blank" >RIV/68407700:21230/08:00145831 - 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
Hybrid Evolution of Heterogeneous Neural Networks
Original language description
In this paper we are describing experiments and results of applications of the continual evolution algorithm to construction and optimization of recurrent neural networks with heterogeneous units. Our algorithm is a hybrid genetic algorithm with sequential individuals replacement, varibale population size and age-based probability control functions. Short introduction to main idea of the algorithm is given. We describe some new features implemented into the algorithm, the encoding of individuals, crossover, and mutation operators. The behavior of population during an evolutionary process is studied on atificial benchmark data sets. Results of the experiments confirm the theoretical properties of the algorithm.
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
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks - ICANN 2008, PT I
ISBN
978-3-540-87535-2
ISSN
0302-9743
e-ISSN
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Number of pages
9
Pages from-to
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Publisher name
Springer
Place of publication
Heidelberg
Event location
Prague
Event date
Sep 3, 2008
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000259566200044