On the fit and forecasting performance of grey prediction models for China’s labor formation

Yin, Mu-Shang; Tang, Hui-Wen Vivian

doi:10.1016/j.mcm.2012.06.013

Cited by 18 publications

(10 citation statements)

References 26 publications

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“…To solve the problem, in 1982, Professor Deng Julong, a Chinese scholar, initiated the grey system theory which is a branch of uncertainty systems science, under the assumption that circumstantial information obtained by decision makers or researchers may be partially unknown, uncertain or incomplete [16,17]. The grey forecasting model adopts the essential part of the grey system theory, and it has been successfully used in finance, physical control, engineering and economics [18,19]. Thus, the main purpose of this research is to forecast the trend prediction of agricultural drought disasters in China.…”

Section: Grey System Theory and Grey Prediction Modelsmentioning

confidence: 99%

Temporal Distribution and Trend Prediction of Agricultural Drought Disasters in China

Xie

Liu

2014

Proceedings of the Eighth International Conference on Management Science and Engineering Management

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China is one of the countries where agricultural drought disasters occur particularly frequently. The prediction of agricultural drought disasters plays an important role in the drought disaster defense and reduction. This paper, based on the agricultural drought disaster statistics between 1978 and 2011 years in China, analyzed the temporal distribution characters of agricultural drought disasters during the period from 1978 to 2011 in China. It can be seen from the analysis that agricultural natural disasters fluctuated in the research period. Three phases can be evidently indicated: the drought disasters had lower harm to agriculture in the 1978-1984; great disaster influenced area and losses increased evidently in the 1985-2000; the drought disasters had lower harm to agriculture in the period of 2001-2011, except for the year of 2001. Based upon the topologic predicting method of grey system theory, this paper established predicting models. Through applying these models in fact, it is testified that topologic prediction is an effective method that can predict the sequences with wide fluctuating range. This paper also predicted the changing trend of agricultural drought disasters in 15 years in China. It found that heavy agricultural drought disaster will occur in all the 15 years except for 2012 and 2022. The trend of disaster-suffering will be over the average levels in the past 34 years and will appear 4 year of great drought respectively 2015, 2017, 2020 and 2025. At the same time, the interval time of the great drought is between 3 and 5 years.

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Section: Grey System Theory and Grey Prediction Modelsmentioning

confidence: 99%

Temporal Distribution and Trend Prediction of Agricultural Drought Disasters in China

Xie

Liu

2014

Proceedings of the Eighth International Conference on Management Science and Engineering Management

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“…The detailed procedure of GM(1,1) has been detailed in other relevant research (Tien, 2005;Wu & Chen, 2005;Kayacan et al, 2010;Truong & Ahn, 2012;Yin & Tang, 2013). So here we only present 2 criteria for testing the model precision of GM(1,1): one is -a (the development coefficient in the model), and the other is the average relative error (ARE) (see Table 2), citing Liu et al (2010).…”

Section: Grey Prediction Model-gm(11): Predicting Future Behaviorsmentioning

confidence: 99%

MDG Hunger Target: Analysis of Cereal Production System and the Evaluation of Cereal Production Potential in Africa

Xing-na¹,

Long²

2013

JSD

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The contradiction between Africa's GDP growth and poverty has raised much debate in the scientific community, which casts much doubt on Africa's prospect in achieving MDG (Millenium Development Goals) hunger target. To better tackle this issue, we resort to grey system theory for solution. Firstly, by grey relational analysis (GRA), we aim to find out the relationship between the population undernourished (PU, the major index of MDG hunger target), and cereal production (CP). Then we establish a grey system composed of 8 factors, to identify the major ones in affecting cereal production. Through GRA and grey prediction model GM(1,1), the grey relations between each set of 2 factors out of the 8, as mentioned above, are analyzed and predicted. Next, we evaluate the short-term performance of Africa in reaching MDG hunger target by utilizing GM(1,1) as well. Finally, long-term continental and national cereal productions are forecasted by GM(1,1) from 2021 to 2051, based on data 1961-2011, which can serve as a signifier for Africa's CPP (cereal production prediction) and the corresponding potential in cutting down PU in the long run. The results from this study suggest that PU and CP are related so that we could cut down PU by promoting CPP, that different factors is likely to show different extents of projected relativeness with cereal production in the future, and that the national disparities of cereal production in Africa are inclined to rise, although the majority of African countries may be able to enjoy a remarkable boost in cereal production prediction. Most importantly, 38% of Africa countries show encouraging signs in achieving MDG hunger target on the national level, indicating that we need to be very cautious in believing in Africa's ability of achieving it on the whole continent. Finally, several methods and suggestions in eradicating hunger and promoting cereal production are come up with.

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“…Tang and Yin [6] forecasted the education expenditure and school enrollment by the GM(1, 1). Yin and Tang [7] fitted and forecasted China's labor formation based on the prediction GM(1, 1). Li et al [8] applied the GM(1, 1) and GRA to evaluate the financial burden of patients at hospitals in China by PPP model.…”

Section: Introductionmentioning

confidence: 99%

An Improved Metabolism Grey Model for Predicting Small Samples with a Singular Datum and Its Application to Sulfur Dioxide Emissions in China

Zhou

Zhang

2016

Discrete Dynamics in Nature and Society

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This study proposes an improved metabolism grey model [IMGM(1,1)] 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(1,1)in small samples and the additional advantages of the MGM(1,1)in new real-time data, while overcoming the limitations of both the conventional GM(1,1)and MGM(1,1)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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On the fit and forecasting performance of grey prediction models for China’s labor formation

Cited by 18 publications

References 26 publications

Temporal Distribution and Trend Prediction of Agricultural Drought Disasters in China

Temporal Distribution and Trend Prediction of Agricultural Drought Disasters in China

MDG Hunger Target: Analysis of Cereal Production System and the Evaluation of Cereal Production Potential in Africa

An Improved Metabolism Grey Model for Predicting Small Samples with a Singular Datum and Its Application to Sulfur Dioxide Emissions in China

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