Evolutionary techniques for neural network optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F05%3AA0900ERV" target="_blank" >RIV/61988987:17310/05:A0900ERV - isvavai.cz</a>
Alternative codes found
RIV/61988987:17310/05:A1000ERV
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Evolutionary techniques for neural network optimization
Original language description
The idea of evolving artificial networks by evolutionary algorithms is based on a powerful metaphor: the evolution of the human brain. The application of evolutionary algorithms to neural network optimization is an active field of study. The success andspeed of training of neural network is based on the initial parameter settings, such as architecture, initial weights, learning rates, and others. A lot of research is being done on how to find the optimal network architecture and parameter settings given the problem it has to learn. One possible solution is use of evolutionary algorithms to neural network optimization systems. We can distinguish two separate issues for it: on the one hand weight training, and on the other hand architecture optimization. Next, we will focus on the architecture optimization and especially on the comparison of different strategies of neural network architecture encoding for the purchase of the evolutionary algorithm.
Czech name
Optimalizace neuronových sítí evolučními technikami
Czech description
Optimalizace neuronových sítí evolučními technikami
Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2005
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 1st International Workshop on Artifitial Neural Networks and Intelligent Information Processing, ANNIIP 2005.
ISBN
972-8865-36-8
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
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Publisher name
In conjuction with ICINCO 2005.
Place of publication
Barcelona
Event location
Barcelona
Event date
Sep 13, 2005
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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