Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model

Systems, Год журнала: 2025, Номер 13(1), С. 51 - 51

Опубликована: Янв. 15, 2025

The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role accuracy of model predictions. However, traditional forward does not adhere to principle prioritizing new information. Therefore, we propose novel fractional reverse accumulation, which increases coefficient fully utilize information carried by latest data. This led development model, termed FGRM(1,1). was validated using renewable energy consumption from France, Spain, UK, and Europe, results demonstrated that FGRM(1,1) outperformed other models terms simulation error, prediction comprehensive error. predictions indicated significant growth France moderate robust Europe overall. These findings highlight effectiveness proposed utilizing provide insights into transition emission reduction potential Europe.

Язык: Английский

Forecasts and Analysis of Economic Outputs for Chinese High-Tech Industries: Insights from Spatial–Temporal Information Fusion

Computational Economics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 14, 2025

Язык: Английский

An innovative nonlinear grey system model with generalized fractional operators and its application

Alexandria Engineering Journal, Год журнала: 2025, Номер 125, С. 463 - 479

Опубликована: Апрель 22, 2025

Язык: Английский