Asynchronous Synthesis of a Neural Network Applied on Head Load Prediction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F13%3A43869917" target="_blank" >RIV/70883521:28140/13:43869917 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-33227-2_24" target="_blank" >http://dx.doi.org/10.1007/978-3-642-33227-2_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-33227-2_24" target="_blank" >10.1007/978-3-642-33227-2_24</a>
Alternative languages
Result language
angličtina
Original language name
Asynchronous Synthesis of a Neural Network Applied on Head Load Prediction
Original language description
This paper introduces innovative method of an artificial neural network (ANN) optimization (synthesis) by means of Analytic Programming (AP). New asynchronous implementation of Self-Organizing Migration Algorithm (SOMA), which provides effective increaseof AP computing potential, is introduced here for time as well as original strategy of communication between SOMA and AP that further contribute towards efficiency in search for optimal ANN solution. The whole ANN synthesis algorithm is applied on the real case of heating plant model identification. The heating plant is located in the town of Most, Czech Republic. The method proves itself to be especially effective when formally identified non-neural parts of the heating plant model need to be made more accurate. Asynchronous distribution plays the key role here as the heating plant behavior data has to be acquired from a very large database and therefore learning of ANN may require a lot of computation time.
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/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: The Centre of Security, Information and Advanced Technologies (CEBIA-Tech)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Nostradamus: Modern Methods of Prediction, Modeling and Analysis of Nonlinear Systems
ISBN
978-3-642-33226-5
ISSN
2194-5357
e-ISSN
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Number of pages
16
Pages from-to
225-240
Publisher name
Springer-Verlag Berlin
Place of publication
Heidelberg
Event location
Ostrava
Event date
Sep 5, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000313767300024