Emission prediction of a thermal power plant

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00077069" target="_blank" >RIV/00216224:14330/14:00077069 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Emission prediction of a thermal power plant

Original language description

The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2014

Confidentiality

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

Article name in the collection

Znalosti 2014

ISBN

9788024520544

ISSN

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e-ISSN

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Number of pages

6

Pages from-to

98-103

Publisher name

Vysoká škola ekonomická v Praze

Place of publication

Praha

Event location

Jasná pod Chopkom, Nízké Tatry, Slovakia

Event date

Jan 1, 2014

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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