Quadratic Neural Unit and its Network in Validation of Process Data of Steam Turbine Loop and Energetic Boiler

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F10%3A00170332" target="_blank" >RIV/68407700:21220/10:00170332 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5596614" target="_blank" >http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5596614</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2010.5596614" target="_blank" >10.1109/IJCNN.2010.5596614</a>

Result language
angličtina
Original language name
Quadratic Neural Unit and its Network in Validation of Process Data of Steam Turbine Loop and Energetic Boiler
Original language description
The paper discusses results and advantages of the application of quadratic neural units and novel quadratic neural network to modeling of real data for purposes of validation of measured data in energetic processes. A feed-forward network of quadratic neural units (a class of higher order neural network) with sequential learning is presented. This quadratic network with this learning technique reduces computational time for models with large number of inputs, sustains optimization convexity of a quadratic model, and also displays sufficient non-linear approximation capability for the real process. A comparison of performances of the quadratic neural units, quadratic neural networks, and the use of common multilayer feed-forward neural networks all trained by Levenberg-Marquardt algorithm is discussed.
Czech name
—
Czech description
—

Project
<a href="/en/project/2B06023" target="_blank" >2B06023: Development of a method for estimation of energy and matter fluxes in selected ecosystems; formulation and verification of principles for evaluation of conditions supporting selfregulation and biodiversity.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2010 IEEE World Congress on Computational Inteligence/ International Joint Conference on Neural Networks 2010
ISBN
978-1-4244-6917-8
ISSN
1098-7576
e-ISSN
—
Number of pages
7
Pages from-to
3391-3397
Publisher name
IEEE
Place of publication
Piscataway
Event location
Barcelona
Event date
Jul 18, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000287421403081

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