Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model
Forecasting the amount of carbon dioxide (CO2 ) emissions has been crucially important to the civilisation of society to ensure that we can inhabit this planet in years to come. Hence, the study that focuses on the prediction on the amount of CO2 releases into the environment has always been the foc...
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Springer Science and Business Media Deutschland GmbH
2022
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author | Sulaiman, Assif Shamim Mustaffa Shabri, Ani Marie, Rashiq Rafiq |
author_facet | Sulaiman, Assif Shamim Mustaffa Shabri, Ani Marie, Rashiq Rafiq |
author_sort | Sulaiman, Assif Shamim Mustaffa |
collection | ePrints |
description | Forecasting the amount of carbon dioxide (CO2 ) emissions has been crucially important to the civilisation of society to ensure that we can inhabit this planet in years to come. Hence, the study that focuses on the prediction on the amount of CO2 releases into the environment has always been the focal point in any international level climate change conferences to ensure the target set would be considerably reached in the future. As the conventional multivariable grey model or GM (1,N) model has widely been used in the study to forecast short-term sample size data, this model possessed issues when dealing with prioritization of information as the weightage was evenly spread across all data points, causes an ineffective forecasting result. This study will use the fractional order multivariable grey model, or FAGM (1,N) model to predict the amount of CO2 emissions for Malaysia within the 10 years timeframe data set. As the FAGM (1,N) model focuses on the prioritization of newer information, the proposed model will be able to forecast the CO2 emissions better compared to the GM (1,N) model even with a small sample size data. |
first_indexed | 2024-03-05T21:17:39Z |
format | Book Section |
id | utm.eprints-99684 |
institution | Universiti Teknologi Malaysia - ePrints |
last_indexed | 2024-03-05T21:17:39Z |
publishDate | 2022 |
publisher | Springer Science and Business Media Deutschland GmbH |
record_format | dspace |
spelling | utm.eprints-996842023-04-04T07:03:48Z http://eprints.utm.my/99684/ Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model Sulaiman, Assif Shamim Mustaffa Shabri, Ani Marie, Rashiq Rafiq QA Mathematics Forecasting the amount of carbon dioxide (CO2 ) emissions has been crucially important to the civilisation of society to ensure that we can inhabit this planet in years to come. Hence, the study that focuses on the prediction on the amount of CO2 releases into the environment has always been the focal point in any international level climate change conferences to ensure the target set would be considerably reached in the future. As the conventional multivariable grey model or GM (1,N) model has widely been used in the study to forecast short-term sample size data, this model possessed issues when dealing with prioritization of information as the weightage was evenly spread across all data points, causes an ineffective forecasting result. This study will use the fractional order multivariable grey model, or FAGM (1,N) model to predict the amount of CO2 emissions for Malaysia within the 10 years timeframe data set. As the FAGM (1,N) model focuses on the prioritization of newer information, the proposed model will be able to forecast the CO2 emissions better compared to the GM (1,N) model even with a small sample size data. Springer Science and Business Media Deutschland GmbH 2022 Book Section PeerReviewed Sulaiman, Assif Shamim Mustaffa and Shabri, Ani and Marie, Rashiq Rafiq (2022) Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model. In: Advances on Intelligent Informatics and Computing Health Informatics, Intelligent Systems, Data Science and Smart Computing. Lecture Notes on Data Engineering and Communications Technologies, 127 (NA). Springer Science and Business Media Deutschland GmbH, Cham, Switzerland, pp. 151-159. ISBN 978-3-030-98740-4 http://dx.doi.org/10.1007/978-3-030-98741-1_14 DOI : 10.1007/978-3-030-98741-1_14 |
spellingShingle | QA Mathematics Sulaiman, Assif Shamim Mustaffa Shabri, Ani Marie, Rashiq Rafiq Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title | Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title_full | Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title_fullStr | Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title_full_unstemmed | Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title_short | Forecasting carbon dioxide emission for Malaysia using fractional order multivariable grey model |
title_sort | forecasting carbon dioxide emission for malaysia using fractional order multivariable grey model |
topic | QA Mathematics |
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