Abstract: Accurate forecasting of natural gas production is essential for ensuring energy supply, optimizing the energy structure, and promoting high-quality economic development. This paper proposes a novel Seasonal Weighted Fractional Nonlinear Grey Bernoulli Model (SWFNGBM(1,1|sinx)) to predict China's natural gas production. First, a seasonal weighted fractional accumulation generation operator is introduced and combined with a sine function to enhance the traditional NGBM(1,1) model, aiming to eliminate seasonal fluctuations in the data and capture nonlinear dynamic characteristics. Second, to address the limitations of the traditional Grey Wolf Optimizer (GWO) algorithm in terms of search efficiency and global optimization capability, an improved algorithm incorporating Levy flight is employed to optimize the hyperparameters of the proposed model. Finally, comparative experiments with other models validate the superior predictive accuracy of the proposed model. Based on the newly developed model, China's seasonal natural gas production is forecasted, and the results demonstrate the strong practicality of the model.

Key words: Seasonal weighted fractional accumulation generation operator, Grey Bernoulli model, Improved grey wolf optimization algorithm, Natural gas production forecasting