Abstract：
:Effective determination of trends in sulfur dioxide emissions facilitates national efforts to draft an appropriate policy that aims to lower sulfur dioxide emissions, which is essential for reducing atmospheric pollution. However, to reflect the current situation, a favorable emission reduction policy should be based on updated information. Various forecasting methods have been developed, but their applications are often limited by insufficient data. Grey system theory is one potential approach for analyzing small data sets. In this study, an improved modeling procedure based on the grey system theory and the mega-trend-diffusion technique is proposed to forecast sulfur dioxide emissions in China. Compared with the results obtained by the support vector regression and the radial basis function network, the experimental results indicate that the proposed procedure can effectively handle forecasting problems involving small data sets. In addition, the forecast predicts a steady decline in China's sulfur dioxide emissions. These findings can be used by the Chinese government to determine whether its current policy to reduce sulfur dioxide emissions is appropriate.
journal_name
Int J Environ Res Public Healthauthors
Chang CJ,Li G,Zhang SQ,Yu KPdoi
10.3390/ijerph16142504subject
Has Abstractpub_date
2019-07-13 00:00:00issue
14eissn
1661-7827issn
1660-4601pii
ijerph16142504journal_volume
16pub_type
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journal_title：International journal of environmental research and public health
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