Optimized Non-linear Multivariable Grey Model for Carbon Dioxide Emissions in Malaysia

Assif Shamim Bin Mustaffa Sulaiman, Ani Bin Shabri
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Abstract

This paper analyses the relationship between carbon dioxide emissions with the energy consumption from the year 2005 to 2014 in Malaysia by introducing an optimized non-linear multivariable grey, NGM(1,N) model by establishing a power exponent term for its subsequent relevant factors. The aim of this research is to improve the existing NGM(1,N) model by solving the effect of non-linear properties which is able to correlate among the consequent factors based on the selection of power exponent optimization. This paper will also introduce the transformed NGM(1,N) known as TNGM(1,N) model that produces a more accurate result compared to NGM(1,N) model that prompted simulated output. The power exponent term value was determined using the generalized reduced gradient (GRG) method in Microsoft Excel Solver. It is proven that the TNGM(1,N) model performs the best and hence it serves as vital information for the government’s environmental-related agencies and policymakers to focus on the effort to promote green efficient technology to society at large by reducing the releases of carbon dioxide emissions to the environment.
马来西亚二氧化碳排放的优化非线性多变量灰色模型
本文通过引入优化的非线性多变量灰色NGM(1,N)模型,为其后续相关因素建立幂指数项,分析了马来西亚2005 - 2014年二氧化碳排放与能源消耗之间的关系。本研究的目的是在幂指数优化选择的基础上,通过解决非线性特性对NGM(1,N)模型的影响,从而改进现有的NGM(1,N)模型。本文还将介绍转换后的NGM(1,N),即TNGM(1,N)模型,与提示模拟输出的NGM(1,N)模型相比,该模型产生更准确的结果。在Microsoft Excel求解器中采用广义约简梯度(GRG)法确定幂指数项值。事实证明,TNGM(1,N)模型表现最好,因此它为政府的环境相关机构和政策制定者提供了重要的信息,以便通过减少二氧化碳向环境排放的释放,将绿色高效技术推广到整个社会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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