Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models
Decision making; Economics; Energy policy; Energy utilization; Natural gas; Population statistics; Time series; Auto-regressive; Energy demands; Energy model; Final energy; Long-term energy demand; Multiple non linear regressions; Non linear; Non-linear autoregressive exogenous; Per capita; Predicti...
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2023
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my.uniten.dspace-259252023-05-29T17:05:34Z Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models Ayodele B.V. Mustapa S.I. Mohammad N. Shakeri M. 56862160400 36651549700 57220108757 55433849200 Decision making; Economics; Energy policy; Energy utilization; Natural gas; Population statistics; Time series; Auto-regressive; Energy demands; Energy model; Final energy; Long-term energy demand; Multiple non linear regressions; Non linear; Non-linear autoregressive exogenous; Per capita; Predictive energy modeling; Neural networks Energy modeling and forecasting are key to providing insightful energy-related policy decisions that could propel positive economic growth and sustainable development. In this study, the Non-Linear Autoregressive Exogenous Neural Networks (NARX) and Multiple Non-Linear Regression (MNLR) models were employed for modeling the final energy demand per capita in Malaysia. The non-linear relationship between the time-series data such as GDP per capita, population, crude oil supply, natural gas supply, coal and coke supply, hydropower, electricity demand per capita, and the final energy demand per capita were modeled using five NARX and MNLR models refer to as NARX-1, NARX-3, NARX-5, MNLR-1, and MNLR-2. The effect of varying the network time delay and the hidden neurons on the NARX model performance were investigated. The best model configuration was obtained using 1 network delay and 17 hidden neurons. Both the NARX-1 and MNLR-1 models accurately learn the time series data for the prediction of the final energy consumption per capita. With R2 of 0.999 and 0.996 obtained for the NARX-1 and MLNR-1, respectively, the predicted final energy demand per capita was in close agreement with the actual values. Using the NARX-1 and MNLR-1 models, the final energy demand per capita was projected to be 2.3 toe/person and 2.1toe/person, respectively by 2050. The level of importance analysis of the NARX-1 models and the parameter estimates of the MNLR-1 model revealed that an increase in population and natural gas supply had a significant influence on the predicted final energy demand per capita. � 2021 The Authors Final 2023-05-29T09:05:34Z 2023-05-29T09:05:34Z 2021 Article 10.1016/j.esr.2021.100750 2-s2.0-85118476264 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118476264&doi=10.1016%2fj.esr.2021.100750&partnerID=40&md5=284bdbe1ccd886da296b7fcf45fe631f https://irepository.uniten.edu.my/handle/123456789/25925 38 100750 All Open Access, Gold Elsevier Ltd Scopus |
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Malaysia |
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Universiti Tenaga Nasional |
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| description |
Decision making; Economics; Energy policy; Energy utilization; Natural gas; Population statistics; Time series; Auto-regressive; Energy demands; Energy model; Final energy; Long-term energy demand; Multiple non linear regressions; Non linear; Non-linear autoregressive exogenous; Per capita; Predictive energy modeling; Neural networks |
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56862160400 |
| author_facet |
56862160400 Ayodele B.V. Mustapa S.I. Mohammad N. Shakeri M. |
| format |
Article |
| author |
Ayodele B.V. Mustapa S.I. Mohammad N. Shakeri M. |
| spellingShingle |
Ayodele B.V. Mustapa S.I. Mohammad N. Shakeri M. Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| author_sort |
Ayodele B.V. |
| title |
Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| title_short |
Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| title_full |
Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| title_fullStr |
Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| title_full_unstemmed |
Long-term energy demand in Malaysia as a function of energy supply: A comparative analysis of Non-Linear Autoregressive Exogenous Neural Networks and Multiple Non-Linear Regression Models |
| title_sort |
long-term energy demand in malaysia as a function of energy supply: a comparative analysis of non-linear autoregressive exogenous neural networks and multiple non-linear regression models |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806425495147905024 |
| score |
13.214268 |