A novel grey model with fractional reverse accumulation for forecasting natural gas consumption

Prioritizing new information is regarded as a significant principle of the grey prediction model and has attracted increasing attention from scholars. To utilize new information and improve the poor extrapolation performance of the original model, a novel fractional reverse accumulation method is proposed, and its properties are explored. This method is combined with the traditional GM (1,1) model to construct a novel grey prediction model, the FGRM (1,1). The model perturbation is analyzed, and the natural gas consumption in the Commonwealth of Independent States (CIS) for 2022–2025 is forecasted. We conclude that this novel accumulation method works well and allows the model to capture the most recent trends in the system, thus achieving accurate forecasts. The FGRM (1,1) model performs better than other fractional grey models in simulations and forecasting. The forecast results indicate that natural gas consumption in the CIS will continuously increase, with a projected increase of 5% by 2025.