A Neural Network Model for Predicting NOx at the Mělník 1 Coal-powder Power Plant

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F12%3A00204500" target="_blank" >RIV/68407700:21220/12:00204500 - isvavai.cz</a>

Result on the web

<a href="http://ctn.cvut.cz/ap/index.php?year=2012&idissue=80" target="_blank" >http://ctn.cvut.cz/ap/index.php?year=2012&idissue=80</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

A Neural Network Model for Predicting NOx at the Mělník 1 Coal-powder Power Plant

Original language description

This paper presents a non-conventional dynamic neural network that was designed for real time prediction of NOx at the coal powder power plant Mělník 1, and results on real data are shown and discussed. The paper also presents the signal preprocessing techniques, the input-reconfigurable architecture, and the learning algorithm of the proposed neural network, which was designed to handle the non-stationarity of the burning process as well as individual failures of the measured variables. The advantagesof our designed neural network over conventional neural networks are discussed.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BC - Theory and management systems

OECD FORD branch

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Project

<a href="/en/project/FR-TI1%2F538" target="_blank" >FR-TI1/538: Measurement technology for advanced combustion control</a><br>

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Acta Polytechnica

ISSN

1210-2709

e-ISSN

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Volume of the periodical

52

Issue of the periodical within the volume

3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

6

Pages from-to

17-22

UT code for WoS article

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EID of the result in the Scopus database

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