This study proposes an improved metabolism grey model [IMGM] to predict small samples with a singular datum, which is a common phenomenon in daily economic data. This new model combines the fitting advantage of the conventional GM in small samples and the additional advantages of the MGM in new real-time data, while overcoming the limitations of both the conventional GM and MGM when the predicted results are vulnerable at any singular datum. Thus, this model can be classified as an improved grey prediction model. Its improvements are illustrated through a case study of sulfur dioxide emissions in China from 2007 to 2013 with a singular datum in 2011. Some features of this model are presented based on the error analysis in the case study. Results suggest that if action is not taken immediately, sulfur dioxide emissions in 2016 will surpass the standard level required by the Twelfth Five-Year Plan proposed by the China State Council.
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Publication date: Available online 4 January 2018 Source: European Journal of Radiology Author(s): Peiyao Zhang, Jing Wang, Qin Xu, Zhen...
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BACKGROUND AND PURPOSE: Lesion load is a common biomarker in multiple sclerosis, yet it has historically shown modest association with cl...
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Vol.48 No.2 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1S2Z7n2 via IFTTT
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Does CBD Oil Lower Blood Pressure? This article was originally published at SundayScaries." Madeline Taylor POSTED ON January 13, 20...
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