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Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters

Huge emissions of carbon dioxide (CO2) from the utilization of fossil fuel for power generation has significantly contributed to global warming. In view of this, technological pathways have been initiated to mitigate the effect of CO2 emissions through capture, storage, and utilization. Besides, the...

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Main Authors:	Ayodele, Ozavize Freida, Ayodele, Bamidele Victor, Siti Indati, Mustapa, Fernando, Yudi
Format:	Article
Language:	English
Published:	Elsevier Ltd 2021
Subjects:	HC Economic History and Conditions T Technology (General) TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/33078/1/Effect%20of%20activation%20function%20in%20modeling%20the%20nexus%20between%20carbon%20tax%2C%20CO2%20emissions.pdf http://umpir.ump.edu.my/id/eprint/33078/ https://doi.org/10.1016/j.ecmx.2021.100111 https://doi.org/10.1016/j.ecmx.2021.100111
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spelling	my.ump.umpir.330782022-02-04T03:02:21Z http://umpir.ump.edu.my/id/eprint/33078/ Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters Ayodele, Ozavize Freida Ayodele, Bamidele Victor Siti Indati, Mustapa Fernando, Yudi HC Economic History and Conditions T Technology (General) TJ Mechanical engineering and machinery Huge emissions of carbon dioxide (CO2) from the utilization of fossil fuel for power generation has significantly contributed to global warming. In view of this, technological pathways have been initiated to mitigate the effect of CO2 emissions through capture, storage, and utilization. Besides, there is an increasing acceptance of carbon tax which is levied in the proportion of carbon emissions from the utilization of fossil fuel. In this study, the nexus between carbon tax, equivalent CO2 emissions from the gas-fired power plant, natural gas flow rate, and air-to-fuel ratio was modeled using a perceptron neural network. The effect of various combinations of identity, hyperbolic tangent, and sigmoid activation functions at the hidden and outer layer of the neural network on the performance of the models was investigated. The various network configurations were trained using the Levenberg-Marquardt algorithm with the network errors backpropagated to enhance the performance. The optimized networks consist of three input units, 15 hidden neurons, and one output unit. The network performance in modeling the carbon tax prediction resulted in R2 of 0.999, 0.999, 0.999, 0.998, and 0.999 for model 1, model 2, model 3, model 4, and model 5, respectively which is an indication that the calculated carbon tax was strongly correlated with the predicted values. The prediction errors of 0.019, 0.009, 0.002, 0.016, 0.002 obtained from model 1, model 2, model 3, model 4, and model 5, respectively revealed the robustness of the models in predicting the carbon tax with minimum error. Among the various configurations investigated, the perceptron neural network configured with hyperbolic tangent and sigmoid activation function at the hidden and outer layers, as well as the configuration with sigmoid activation functions at the hidden and outer layers, offer the best performance. The sensitivity analysis shows that the flow rate of the natural gas had the most significant effect on the predicted carbon tax. Elsevier Ltd 2021-12 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/33078/1/Effect%20of%20activation%20function%20in%20modeling%20the%20nexus%20between%20carbon%20tax%2C%20CO2%20emissions.pdf Ayodele, Ozavize Freida and Ayodele, Bamidele Victor and Siti Indati, Mustapa and Fernando, Yudi (2021) Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters. Energy Conversion and Management: X, 12 (100111). pp. 1-9. ISSN 2590-1745 https://doi.org/10.1016/j.ecmx.2021.100111 https://doi.org/10.1016/j.ecmx.2021.100111
institution	Universiti Malaysia Pahang
building	UMP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang
content_source	UMP Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English
topic	HC Economic History and Conditions T Technology (General) TJ Mechanical engineering and machinery
spellingShingle	HC Economic History and Conditions T Technology (General) TJ Mechanical engineering and machinery Ayodele, Ozavize Freida Ayodele, Bamidele Victor Siti Indati, Mustapa Fernando, Yudi Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
description	Huge emissions of carbon dioxide (CO2) from the utilization of fossil fuel for power generation has significantly contributed to global warming. In view of this, technological pathways have been initiated to mitigate the effect of CO2 emissions through capture, storage, and utilization. Besides, there is an increasing acceptance of carbon tax which is levied in the proportion of carbon emissions from the utilization of fossil fuel. In this study, the nexus between carbon tax, equivalent CO2 emissions from the gas-fired power plant, natural gas flow rate, and air-to-fuel ratio was modeled using a perceptron neural network. The effect of various combinations of identity, hyperbolic tangent, and sigmoid activation functions at the hidden and outer layer of the neural network on the performance of the models was investigated. The various network configurations were trained using the Levenberg-Marquardt algorithm with the network errors backpropagated to enhance the performance. The optimized networks consist of three input units, 15 hidden neurons, and one output unit. The network performance in modeling the carbon tax prediction resulted in R2 of 0.999, 0.999, 0.999, 0.998, and 0.999 for model 1, model 2, model 3, model 4, and model 5, respectively which is an indication that the calculated carbon tax was strongly correlated with the predicted values. The prediction errors of 0.019, 0.009, 0.002, 0.016, 0.002 obtained from model 1, model 2, model 3, model 4, and model 5, respectively revealed the robustness of the models in predicting the carbon tax with minimum error. Among the various configurations investigated, the perceptron neural network configured with hyperbolic tangent and sigmoid activation function at the hidden and outer layers, as well as the configuration with sigmoid activation functions at the hidden and outer layers, offer the best performance. The sensitivity analysis shows that the flow rate of the natural gas had the most significant effect on the predicted carbon tax.
format	Article
author	Ayodele, Ozavize Freida Ayodele, Bamidele Victor Siti Indati, Mustapa Fernando, Yudi
author_facet	Ayodele, Ozavize Freida Ayodele, Bamidele Victor Siti Indati, Mustapa Fernando, Yudi
author_sort	Ayodele, Ozavize Freida
title	Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
title_short	Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
title_full	Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
title_fullStr	Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
title_full_unstemmed	Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters
title_sort	effect of activation function in modeling the nexus between carbon tax, co2 emissions, and gas-fired power plant parameters
publisher	Elsevier Ltd
publishDate	2021
url	http://umpir.ump.edu.my/id/eprint/33078/1/Effect%20of%20activation%20function%20in%20modeling%20the%20nexus%20between%20carbon%20tax%2C%20CO2%20emissions.pdf http://umpir.ump.edu.my/id/eprint/33078/ https://doi.org/10.1016/j.ecmx.2021.100111 https://doi.org/10.1016/j.ecmx.2021.100111
_version_	1724073518932426752
score	13.223943

Effect of activation function in modeling the nexus between carbon tax, CO2 emissions, and gas-fired power plant parameters

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