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

Systems, Journal Year: 2025, Volume and Issue: 13(1), P. 51 - 51

Published: Jan. 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.

Language: Английский

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

Computational Economics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 14, 2025

Language: Английский

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

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 125, P. 463 - 479

Published: April 22, 2025

Language: Английский