Study on prediction fly ash generation using statistical method

This study present of fly ash generation at generated one the power plant in Malaysia. The main purpose of this research to predict the generation of fly ash in future years by a method. This prediction is important so that fly ash generated could be used in a beneficial way. Prediction of fly ash w...

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Main Authors: Zahari N.M., Mohamad D., Arenandan V., Beddu S., Sadon S.N., Syamsir A., Kamal N.L.M., Zainoodin M.M., Nadhirah A.
Other Authors: 54891672300
Format: Conference Paper
Published: American Institute of Physics Inc. 2023
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spelling my.uniten.dspace-235362023-05-29T14:50:08Z Study on prediction fly ash generation using statistical method Zahari N.M. Mohamad D. Arenandan V. Beddu S. Sadon S.N. Syamsir A. Kamal N.L.M. Zainoodin M.M. Nadhirah A. 54891672300 57200335404 57209317359 55812080500 57200334298 57195320482 56239107300 57202388764 56353119500 This study present of fly ash generation at generated one the power plant in Malaysia. The main purpose of this research to predict the generation of fly ash in future years by a method. This prediction is important so that fly ash generated could be used in a beneficial way. Prediction of fly ash was done by using two types of software which are Neural Network Toolbox, MATLAB and IBM SPSS Statistics 23, Linear Regression. Among these two methods, IBM SPSS Statistics 23, Linear Regression is found to be the most effective way to predict the generation of fly ash in the future by using five year's best fit linear regression equation compared to Neural Network Toolbox, MATLAB. � 2018 Author(s). Final 2023-05-29T06:50:08Z 2023-05-29T06:50:08Z 2018 Conference Paper 10.1063/1.5066994 2-s2.0-85057225486 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057225486&doi=10.1063%2f1.5066994&partnerID=40&md5=b07e2b62cbb1a968e9cc5b17ff10d9bb https://irepository.uniten.edu.my/handle/123456789/23536 2031 20038 All Open Access, Bronze American Institute of Physics Inc. 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 This study present of fly ash generation at generated one the power plant in Malaysia. The main purpose of this research to predict the generation of fly ash in future years by a method. This prediction is important so that fly ash generated could be used in a beneficial way. Prediction of fly ash was done by using two types of software which are Neural Network Toolbox, MATLAB and IBM SPSS Statistics 23, Linear Regression. Among these two methods, IBM SPSS Statistics 23, Linear Regression is found to be the most effective way to predict the generation of fly ash in the future by using five year's best fit linear regression equation compared to Neural Network Toolbox, MATLAB. � 2018 Author(s).
author2 54891672300
author_facet 54891672300
Zahari N.M.
Mohamad D.
Arenandan V.
Beddu S.
Sadon S.N.
Syamsir A.
Kamal N.L.M.
Zainoodin M.M.
Nadhirah A.
format Conference Paper
author Zahari N.M.
Mohamad D.
Arenandan V.
Beddu S.
Sadon S.N.
Syamsir A.
Kamal N.L.M.
Zainoodin M.M.
Nadhirah A.
spellingShingle Zahari N.M.
Mohamad D.
Arenandan V.
Beddu S.
Sadon S.N.
Syamsir A.
Kamal N.L.M.
Zainoodin M.M.
Nadhirah A.
Study on prediction fly ash generation using statistical method
author_sort Zahari N.M.
title Study on prediction fly ash generation using statistical method
title_short Study on prediction fly ash generation using statistical method
title_full Study on prediction fly ash generation using statistical method
title_fullStr Study on prediction fly ash generation using statistical method
title_full_unstemmed Study on prediction fly ash generation using statistical method
title_sort study on prediction fly ash generation using statistical method
publisher American Institute of Physics Inc.
publishDate 2023
_version_ 1806426137338839040
score 13.214268