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A support vector based CO2 gas emission prediction system for generation power plant

The work presents an intelligent system Support Vector Regression Emission Monitoring System (SuVEMS) developed for Tenaga Nasional Berhad (TNB) Sdn. Bhd. in Peninsular Malaysia for the prediction of harmful gas emissions from electricity generating power plants in Tuanku Jaafar Power Station (TJPS)...

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Main Authors: Chen C.P., Tiong S.K., Albert F.Y.C., Koh S.P.
Other Authors: 25824552100
Format: Article
Published: American Scientific Publishers 2023
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spelling my.uniten.dspace-232342023-05-29T14:38:39Z A support vector based CO2 gas emission prediction system for generation power plant Chen C.P. Tiong S.K. Albert F.Y.C. Koh S.P. 25824552100 15128307800 56572305600 22951210700 The work presents an intelligent system Support Vector Regression Emission Monitoring System (SuVEMS) developed for Tenaga Nasional Berhad (TNB) Sdn. Bhd. in Peninsular Malaysia for the prediction of harmful gas emissions from electricity generating power plants in Tuanku Jaafar Power Station (TJPS). The CO2, emissions is modelled on this work using Support Vector Regression (SVR), a statistical machine learning tool with a regression-based extension towards Support Vector Machines (SVMs). The gas is predicted using independent models and the gas prediction model is trained using feature subsets selected using the forward selection approach. The SuVEMS results are compared and measured the performance with the Continuous Emission Monitoring System, CEMS results. The SuVEMS results implemented at TJPS indicate that it has the ability for the online prediction with average prediction accuracy of 95%. � 2017 American Scientific Publishers All rights reserved. Final 2023-05-29T06:38:39Z 2023-05-29T06:38:39Z 2017 Article 10.1166/asl.2017.8875 2-s2.0-85023763610 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023763610&doi=10.1166%2fasl.2017.8875&partnerID=40&md5=ae2cfa8a998b657558472b2f09d6dfa4 https://irepository.uniten.edu.my/handle/123456789/23234 23 5 4518 4522 American Scientific Publishers Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description The work presents an intelligent system Support Vector Regression Emission Monitoring System (SuVEMS) developed for Tenaga Nasional Berhad (TNB) Sdn. Bhd. in Peninsular Malaysia for the prediction of harmful gas emissions from electricity generating power plants in Tuanku Jaafar Power Station (TJPS). The CO2, emissions is modelled on this work using Support Vector Regression (SVR), a statistical machine learning tool with a regression-based extension towards Support Vector Machines (SVMs). The gas is predicted using independent models and the gas prediction model is trained using feature subsets selected using the forward selection approach. The SuVEMS results are compared and measured the performance with the Continuous Emission Monitoring System, CEMS results. The SuVEMS results implemented at TJPS indicate that it has the ability for the online prediction with average prediction accuracy of 95%. � 2017 American Scientific Publishers All rights reserved.
author2 25824552100
author_facet 25824552100
Chen C.P.
Tiong S.K.
Albert F.Y.C.
Koh S.P.
format Article
author Chen C.P.
Tiong S.K.
Albert F.Y.C.
Koh S.P.
spellingShingle Chen C.P.
Tiong S.K.
Albert F.Y.C.
Koh S.P.
A support vector based CO2 gas emission prediction system for generation power plant
author_sort Chen C.P.
title A support vector based CO2 gas emission prediction system for generation power plant
title_short A support vector based CO2 gas emission prediction system for generation power plant
title_full A support vector based CO2 gas emission prediction system for generation power plant
title_fullStr A support vector based CO2 gas emission prediction system for generation power plant
title_full_unstemmed A support vector based CO2 gas emission prediction system for generation power plant
title_sort support vector based co2 gas emission prediction system for generation power plant
publisher American Scientific Publishers
publishDate 2023
_version_ 1806425592603607040
score 13.222552

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