The modeling mechanism, extension and optimization of grey GM (1, 1) model

Xiao, Xinping; Guo, Huan; Mao, Shuhua

doi:10.1016/j.apm.2013.10.004

Cited by 72 publications

(39 citation statements)

References 2 publications

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“…However, although the gray prediction model has made great progress in its modeling mechanism and performance optimization since the 1980s[3, 32] and some new practical gray system models have been developed [33–34], there are still some problems with the structural and parameter optimization of the traditional gray prediction model [35–40]. Therefore, an improved gray model termed, EGM(1,1, r ), is built, and the modeling conditions and error checking methods of EGM(1,1, r ) are studied.…”

Section: Data Characteristics and Methods Selectionmentioning

confidence: 99%

An improved gray prediction model for China’s beef consumption forecasting

Zeng

Meng

et al. 2019

PLoS ONE

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To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1, r ), is built, and the modeling conditions and error checking methods of EGM(1,1, r ) are studied. Then, EGM(1,1, r ) is used to simulate and forecast China’s beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China’s beef consumption for the period from 2019–2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef.

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Section: Data Characteristics and Methods Selectionmentioning

confidence: 99%

An improved gray prediction model for China’s beef consumption forecasting

Zeng

Meng

et al. 2019

PLoS ONE

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“…The grey system theory is established by Deng in 1982 [3], mainly based on small sample with partial information known and partial information unknown [4]. It mainly focuses on analysis of uncertainty and poor information system [5].…”

Section: A Gm(11) Modelmentioning

confidence: 99%

Prediction of Low-Rent Housing's Supply Quantity Based on Grey Systems Theory

Li¹

2013

2013 Sixth International Conference on Business Intelligence and Financial Engineering

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In this paper, we use grey GM (1, 1) model to predict low rental housings' supply quantity in Beijing from 2013 to 2015.Firstly, we give a brief introduction of renewal grey GM (1, 1) model and its methodology. Secondly, we use per capital floor space of urban residential buildings and nonagricultural population as basic data to predicts Beijing's total housing supply from 2014 to 2016. Finally, we use grey GM (1, 1) model predict the number and the area of low rent housings' supply target in Beijing

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“…Two remarkable aspects can be highlighted: theory and application. Theoretically, several improved versions have been proposed, including the hybrid one (Xia, Chen, Zhang, & Wang, 2008), discrete one (Xie & Liu, 2009), intelligent algorithm-based ones (Bahrami, Hooshmand, & Parastegari, 2014;Hsu, 2010), least-squares-based one (Xu, Tan, Tu, & Qi, 2011), smart adaptive one (Truong & Ahn, 2012) as well as the fractional order-based one (Xiao, Guo, & Mao, 2014). On the other hand, the applications of GM(1, 1) are also enormous, such as accurate reliability prediction (Li, Masuda, Yamaguchi, & Nagai, 2010), fashion color forecasting (Yu, Hui, & Choi, 2012), hyperspectral feature extraction (Yin, Gao, & Jia, 2013), and end effects mitigation in our previous works .…”

Section: Introductionmentioning

confidence: 99%