The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

Pei, Ling-Ling; Li, Qin; Wang, Zheng‐Xin

doi:10.3390/ijerph15030471

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…Grey system theory and grey prediction models have been widely used in many fields, such as economics [20], demand prediction [21,22] and environmental protection [23,24], since being proposed. The traditional GM (1,1) and the grey Verhulst model are the core grey prediction models.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models

Zhao

Shou

Wang

2020

IJERPH

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The outbreak of a novel coronavirus (SARS-CoV-2) has caused a large number of residents in China to be infected with a highly contagious pneumonia recently. Despite active control measures taken by the Chinese government, the number of infected patients is still increasing day by day. At present, the changing trend of the epidemic is attracting the attention of everyone. Based on data from 21 January to 20 February 2020, six rolling grey Verhulst models were built using 7-, 8- and 9-day data sequences to predict the daily growth trend of the number of patients confirmed with COVID-19 infection in China. The results show that these six models consistently predict the S-shaped change characteristics of the cumulative number of confirmed patients, and the daily growth decreased day by day after 4 February. The predicted results obtained by different models are very approximate, with very high prediction accuracy. In the training stage, the maximum and minimum mean absolute percentage errors (MAPEs) are 4.74% and 1.80%, respectively; in the testing stage, the maximum and minimum MAPEs are 4.72% and 1.65%, respectively. This indicates that the predicted results show high robustness. If the number of clinically diagnosed cases in Wuhan City, Hubei Province, China, where COVID-19 was first detected, is not counted from 12 February, the cumulative number of confirmed COVID-19 cases in China will reach a maximum of 60,364–61,327 during 17–22 March; otherwise, the cumulative number of confirmed cases in China will be 78,817–79,780.

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Section: Literature Reviewmentioning

confidence: 99%

Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models

Zhao

Shou

Wang

2020

IJERPH

Self Cite

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“…Xiao et al [ 27 ] established a two-stage dynamic game model to examine the impact of greenhouse gas emission regulations and financial development on the supply chain operations. Based on the nonlinear least square (NLS) method, Pei et al [ 28 ] constructed a novel grey multivariable model, and investigated the relationship between pollutant discharge and economic growth. Sustainable supply chain management is an important research topic in supply chain management.…”

Section: About the Papers Of This Special Issuementioning

confidence: 99%

Special Issue “Decision Models in Green Growth and Sustainable Development”

Zhang

Gong

Yin

et al. 2018

IJERPH

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“…Wu et al [34] proposed a multivariate grey prediction model with a weakening buffer operator. Pei et al [35] put forward the TNGM(1,n) model based on a nonlinear least-square approach, which had better performance than the traditional GM(1,n) model. Wu et al [36] designed the GMCN(1,n) model with the new information priority accumulating operator.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Japan’s Solar Energy Consumption Using a Novel Incomplete Gamma Grey Model

Zhang

She

2019

Sustainability

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Energy consumption is an essential basis for formulating energy policy and programming, especially in the transition of energy consumption structure in a country. Correct prediction of energy consumption can provide effective reference data for decision-makers and planners to achieve sustainable energy development. Grey prediction method is one of the most effective approaches to handle the problem with a small amount of historical data. However, there is still room to improve the prediction performance and enlarge the application fields of the traditional grey model. Nonlinear grey action quantity can effectively improve the performance of the grey prediction model. Therefore, this paper proposes a novel incomplete gamma grey model (IGGM) with a nonlinear grey input over time. The grey input of the IGGM model is a revised incomplete gamma function of time in which the nonlinear coefficient determines the performance of the IGGM model. The WOA algorithm is employed to seek for the optimal incomplete coefficient of the IGGM model. Then, the validations of IGGM are performed on four real-world datasets, and the results exhibit that the IGGM model has more advantages than the other state-of-the-art grey models. Finally, the IGGM model is applied to forecast Japan’s solar energy consumption in the next three years.

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The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

Cited by 5 publications

References 43 publications

Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models

Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models

Special Issue “Decision Models in Green Growth and Sustainable Development”

Forecasting Japan’s Solar Energy Consumption Using a Novel Incomplete Gamma Grey Model

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