A New Algorithm of Parameter Estimation for the Logistic Equation in Modeling CO 2 Emissions from Fossil Fuel Combustion

Ming Meng, Wei Shang, Dongxiao Niu and Qian Gao

Mathematical Problems in Engineering, 2014, vol. 2014, 1-5

Abstract:

CO 2 emissions from fossil fuel combustion have been considered as the most important driving factor of global climate change. A complete understanding of the rules of CO 2 emissions is warranted in modifying the climate change mitigation policy. The current paper advanced a new algorithm of parameter estimation for the logistic equation, which was used to simulate the trend of CO 2 emissions from fossil fuel combustion. The differential equation of the transformed logistic equation was used as the beginning of the parameter estimation. A discretization method was then designed to input the observed samples. After minimizing the residual sum of squares and letting the summation of the residual be equal to 0, the estimated parameters were obtained. Finally, this parameter estimation algorithm was applied to the carbon emissions in China to examine the simulation precision. The error analysis indicators mean absolute percentage error (MAPE), median absolute percentage error (MdAPE), maximal absolute percentage error (MaxAPE), and geometric mean relative absolute error (GMRAE) all showed that the new algorithm was better than the previous ones.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:616312

DOI: 10.1155/2014/616312

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