A novel multi-variable grey forecasting model and its application in forecasting the grain production in China

Zeng, Bo; Li, Hui; Ma, Xin

doi:10.1016/j.cie.2020.106915

Cited by 74 publications

(32 citation statements)

References 24 publications

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“…For the analysis and prediction of problems with "small data and uncertainty," Deng (1982) first introduced the grey system theory based on cybernetics in 1982. The grey system theory has been widely used in many fields so far, and it has successfully solved a large number of practical problems in production, social life, and scientific research (Zeng and Li 2021;Zeng et al 2020aZeng et al , 2020c, and gradually, it has been developed into an important mainstream modeling method. Ding et al (2017) forecasted the Chinese CO 2 emissions from fuel combustion based on the grey forecasting model.…”

Section: Literature Reviewmentioning

confidence: 99%

An improved multi-variable grey model for forecasting China’s finished products from comprehensive waste utilization

Gou

Zeng

Gong

2021

Environ Sci Pollut Res

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A reasonable prediction of the finished products from waste recycling and reprocessing is of great significance to the sustainable use of limited resources, the reduced pollution caused by waste, and the reflected comprehensive waste utilization (CWU) creativity. To this end, an improved multi-variable grey model was employed to forecast the finished products in China's CWU. Firstly, the degree of grey incidence was applied to select explanatory variables and eliminate multicollinearity between them. Then, compared with the traditional GM(1,N) model, the linear correction term and grey action quantity were added in the proposed improved model, and the response function and parameter estimation method of the improved model were deduced and proved. Thirdly, the finished products from CWU was simulated and predicted by the proposed model. The mean relative simulation percentage error of the improved model was only 0.0001%, in comparison with the ones obtained from the traditional GM(1,N) and the classical GM(1,1), which were 12.1232 and 8.8402%, respectively. Lastly, the results show that the finished products from CWU are mainly affected by the comprehensive utilization of general industrial solid waste and the number of industrial enterprises in CWU, and the future trends from 2020 to 2025 are unstable.

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Section: Literature Reviewmentioning

confidence: 99%

An improved multi-variable grey model for forecasting China’s finished products from comprehensive waste utilization

Gou

Zeng

Gong

2021

Environ Sci Pollut Res

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“…e parameter sequence p � (a, b, c) T can be calculated by equation (8), and the unknown parameters α i (i � 1, 2, 3) of NEGM(1, 1) are determined by the constraint optimization problem (17).…”

Section: Forecasting China's Total Electricity Consumptionmentioning

confidence: 99%

“…e grey system theory, proposed by Professor Deng [15] in 1982, plays a key role in processing uncertain problems with poor information and small samples. After more than 30 years of development, many scholars have applied it to industry, agriculture, society, economy, energy, and other fields [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A Novel Extrapolation-Based Grey Prediction Model for Forecasting China’s Total Electricity Consumption

Yang

2021

Mathematical Problems in Engineering

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Accurately forecasting China’s total electricity consumption is of great significance for the government in formulating sustainable economic development policies, especially, China as the largest total electricity consumption country in the world. The calculation method of the background value of the GM(1, 1) model is an important factor of unstable model performance. In this paper, an extrapolation method with variable weights was used for calculating the background value to eliminate the influence of the extreme values on the performance of the GM(1, 1) model, and the novel extrapolation-based grey prediction model called NEGM(1, 1) was proposed and optimized. The NEGM(1, 1) model was then used to simulate the total electricity consumption in China and found to outperform other grey models. Finally, the total electricity consumption of China from 2018 to 2025 was forecasted. The results show that China’s total electricity consumption will be expected to increase slightly, but the total is still very large. For this, some corresponding recommendations to ensure the effective supply of electricity in China are suggested.

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“…e grey prediction model is one of the core parts of the grey system, which is characterized by a few data modelling and simple modelling. At present, it is widely used in energy [2][3][4][5], transportation [6][7][8][9], environment [10,11], and other industries [12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

An Optimization Grey Bernoulli Model and Its Application in Forecasting Oil Consumption

Pang

Duan

2021

Mathematical Problems in Engineering

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Energy consumption in the world is mainly dependent on fossil energy, and oil is one of the main energy sources. Accurate prediction of oil consumption can provide an important basis for national energy security, which can provide reference and early warning for the implementation of the environmental strategy developed by the government. According to the nonlinearity of the energy system, this paper uses the principle of the grey nonlinear prediction model NGBM(1,1) to improve the background value of the model, and by the simulated annealing algorithm, we put forward the optimized grey nonlinear model ONGBM(1,1). At the same time, the model is applied to the oil consumption of China, Chile, Mexico, and Japan. Based on the validity analysis of the existing data of the four countries, the model ONGBM(1,1) is basically superior to the other six grey forecast models. Finally, ONGBM(1,1) is used to predict the oil consumption of the four countries in the next five years, which can provide effective information for energy economic policy.

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A novel multi-variable grey forecasting model and its application in forecasting the grain production in China

Cited by 74 publications

References 24 publications

An improved multi-variable grey model for forecasting China’s finished products from comprehensive waste utilization

An improved multi-variable grey model for forecasting China’s finished products from comprehensive waste utilization

A Novel Extrapolation-Based Grey Prediction Model for Forecasting China’s Total Electricity Consumption

An Optimization Grey Bernoulli Model and Its Application in Forecasting Oil Consumption

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