Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach
Carbon dioxide (CO2) emissions is one of the recent global issues where the negative influence and effect on the environment is high. Enhancing the degree of awareness among public and concerned authorities and developing forecasting methods and techniques form a vital solution to this issue. The ai...
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| Format: | Article |
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Springer Science and Business Media Deutschland GmbH
2021
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| _version_ | 1796866846011424768 |
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| author | Shabri, Ani Samsudin, Ruhaidah Hezzam, Essa Abdullah |
| author_facet | Shabri, Ani Samsudin, Ruhaidah Hezzam, Essa Abdullah |
| author_sort | Shabri, Ani |
| collection | ePrints |
| description | Carbon dioxide (CO2) emissions is one of the recent global issues where the negative influence and effect on the environment is high. Enhancing the degree of awareness among public and concerned authorities and developing forecasting methods and techniques form a vital solution to this issue. The aim of this research is to enhance the forecasting efficiency of the traditional GM(1,N) model by proposing and modifying background values of GM(1,N) using a new algorithms. This paper presents the Artificial Bee Colony (ABC) to select the optimal weight of background values for a traditional GM(1,N) model. The data of CO2 emissions, GDP per capita, the amount invested in Malaysia, population, total energy consumption and number of registered motor vehicles during the period from 2000 to 2016 is used to verify the applicability and effectiveness of the model. The numerical example results indicate that the new model is performing well compared to the traditional GM(1,N) model. |
| first_indexed | 2024-03-05T21:18:18Z |
| format | Article |
| id | utm.eprints-100280 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T21:18:18Z |
| publishDate | 2021 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| record_format | dspace |
| spelling | utm.eprints-1002802023-03-29T07:21:14Z http://eprints.utm.my/100280/ Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach Shabri, Ani Samsudin, Ruhaidah Hezzam, Essa Abdullah QA Mathematics Carbon dioxide (CO2) emissions is one of the recent global issues where the negative influence and effect on the environment is high. Enhancing the degree of awareness among public and concerned authorities and developing forecasting methods and techniques form a vital solution to this issue. The aim of this research is to enhance the forecasting efficiency of the traditional GM(1,N) model by proposing and modifying background values of GM(1,N) using a new algorithms. This paper presents the Artificial Bee Colony (ABC) to select the optimal weight of background values for a traditional GM(1,N) model. The data of CO2 emissions, GDP per capita, the amount invested in Malaysia, population, total energy consumption and number of registered motor vehicles during the period from 2000 to 2016 is used to verify the applicability and effectiveness of the model. The numerical example results indicate that the new model is performing well compared to the traditional GM(1,N) model. Springer Science and Business Media Deutschland GmbH 2021 Article PeerReviewed Shabri, Ani and Samsudin, Ruhaidah and Hezzam, Essa Abdullah (2021) Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach. Lecture Notes on Data Engineering and Communications Technologies, 72 (NA). pp. 586-598. ISSN 2367-4512 http://dx.doi.org/10.1007/978-3-030-70713-2_54 DOI : 10.1007/978-3-030-70713-2_54 |
| spellingShingle | QA Mathematics Shabri, Ani Samsudin, Ruhaidah Hezzam, Essa Abdullah Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title | Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title_full | Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title_fullStr | Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title_full_unstemmed | Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title_short | Short-term CO2 emissions forecasting using multi-variable grey model and Artificial Bee Colony (ABC) algorithm approach |
| title_sort | short term co2 emissions forecasting using multi variable grey model and artificial bee colony abc algorithm approach |
| topic | QA Mathematics |
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