Forecast of natural gas consumption in the Asia-Pacific region using a fractional-order incomplete gamma grey model

To forecast natural gas consumption more accurately, to clearly understand the future supply situation, and to optimize the allocation of resources, a new fractional-order accumulation-based incomplete gamma grey forecasting model is proposed in this paper. To further optimize the traditional grey action quantity, dynamic nonlinear action-based incomplete gamma functions are taken as the grey action quantity and combined with fractional-order accumulation. The role of new information is fully considered, and a detailed modeling process is presented, including computational steps and intelligent optimization algorithms. In this study, this new model is used to simulate and forecast natural gas consumption in the Asia-Pacific region from 2008 to 2018. First, Bangladesh and the Philippines are taken as examples to show the error changes incurred by the model under the control of two parameters. Then, a simulation and prediction of natural gas consumption are conducted and compared with those of other traditional univariate grey models. The results show that the MAPE obtained by the new model is the lowest, which indicates the prediction accuracy and effectiveness of the model. This model has good prediction performance for natural gas consumption and can be extended to more energy consumption prediction problems. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

A new fractional-order accumulation-based incomplete gamma grey forecasting model is proposed in this paper, which combines dynamic nonlinear action-based incomplete gamma functions with fractional-order accumulation, fully considers the role of new information, and demonstrates good prediction performance for natural gas consumption in the Asia-Pacific region.