Mechanism of single variable grey forecasting modelling: Integration of increment and growth rate

Li, Kailing; Xie, Naiming

doi:10.1016/j.cnsns.2023.107409

Cited by 10 publications

(1 citation statement)

References 36 publications

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“…The grey prediction model performs excellently in predicting uncertain systems with small samples (Deng, 1982). It has been applied in fields such as traffic (Mao et al, 2018;He et al, 2023b), tourism demand (Hu, 2023;Jiang and Hu, 2023), material life (Li and Xie, 2023) and energy consumption (Ofosu-Adarkwa and Yao and Mao, 2023). GM(1,1) can be improved according to the needs of the actual sequence.…”

Section: Crude Oil Futures Prices Prediction 91mentioning

confidence: 99%

A matrixed nonlinear exponential grey Bernoulli model for interval number prediction of crude oil futures prices

Cang,

Zeng,

Yan

2023

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PurposeThe effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high volatility and uncertainty of the crude oil futures price, a matrixed nonlinear exponential grey Bernoulli model combined with an exponential accumulation generating operator (MNEGBM(1,1)) is proposed in this paper.Design/methodology/approachFirst, the original sequence is processed by the exponential accumulation generating operator to weaken its volatility. The nonlinear grey Bernoulli and exponential function models are combined to fit the preprocessed sequence. Then, the parameters in MNEGBM(1,1) are matrixed, so the ternary interval number sequence can be modeled directly. Marine Predators Algorithm (MPA) is chosen to optimize the nonlinear parameters. Finally, the Cramer rule is used to derive the time recursive formula.FindingsThe predictive effectiveness of the proposed model is verified by comparing it with five comparison models. Crude oil futures prices in Cushing, OK are predicted and analyzed from 2023/07 to 2023/12. The prediction results show it will gradually decrease over the next six months.Originality/valueCrude oil futures prices are highly volatile in the short term. The use of grey model for short-term prediction is valuable for research. For the data characteristics of crude oil futures price, this study first proposes an improved model for interval number prediction of crude oil futures prices.

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