A seasonal grey model for forecasting energy imports demand from information differences perspective DOI
Weijie Zhou, Jiaxin Chang,

Weizhen Zuo

et al.

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: unknown, P. 115907 - 115907

Published: Dec. 1, 2024

Language: Английский

Dynamic time-delay discrete grey model based on GOWA operator for renewable energy generation cost prediction DOI
Yue Yu,

Xinping Xiao,

Mingyun Gao

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122408 - 122408

Published: Jan. 1, 2025

Language: Английский

Citations

1
Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model DOI Creative Commons
Yudong Zhang, Huiping Wang

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

Citations

0
Damping autoregressive grey model and its application to the prediction of losses caused by meteorological disasters DOI
Shuli Yan, Xiaoyu Gong, Xiangyan Zeng

et al.

Grey Systems Theory and Application, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Purpose Meteorological disasters pose a significant risk to people’s lives and safety, accurate prediction of weather-related disaster losses is crucial for bolstering prevention mitigation capabilities addressing the challenges posed by climate change. Based on uncertainty meteorological sequences, damping accumulated autoregressive GM(1,1) model (DAARGM(1,1)) proposed. Design/methodology/approach Firstly, terms system characteristics are added damping-accumulated model, partial autocorrelation function (PACF) used determine order terms. In addition, optimal parameters determined optimization algorithm. Findings The properties were analyzed in stability solution error restored value. By fitting predicting affected comparing them with results four other grey models, validity new was verified. Originality/value dynamic trend factor introduced into generation operator so that can flexibly adjust accumulative sequence. On basis term take account influence previous data, which more descriptive development time series itself increases effectiveness model.

Language: Английский

Citations

0
Consistent African vulture optimization algorithm for electrical energy exchange in commercial buildings DOI
Linfei Yin, Jing Tian,

Xiaofang Chen

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134741 - 134741

Published: Jan. 1, 2025

Language: Английский

Citations

0
The development trend of China’s marine economy: a predictive analysis based on industry level DOI Creative Commons
Yu Chen,

Huahan Zhang,

Lingling Pei

et al.

Frontiers in Marine Science, Journal Year: 2025, Volume and Issue: 12

Published: Feb. 10, 2025

This paper aims to provide insights into the future trends for marine industries in China, by forecasting added value key sectors and then offering tailored policy recommendations. Those economic indicators at industry level are characterized small sample sizes, sectoral heterogeneity, irregular fluctuations, which require a specialized methodology handle data features predictions each industry. To address these issues, conformable fractional grey model ( CFGM ), integrates accumulation with model, is applied proven effective through accuracy robustness tests. First, results from multi-step experiments demonstrate that significantly outperforms traditional statistical, machine learning models, models context of predictions, an average improvement 32.14%. Second, stability predictive values generated further verified Probability Density Analysis PDA ) multiple comparisons best MCB tests, thereby ruling out possibility accurate result mere chance. Third, used estimate across industries, accompanied suggestions ensure sustainable development economy.

Language: Английский

Citations

0
A seasonal grey model for forecasting energy imports demand from information differences perspective DOI
Weijie Zhou, Jiaxin Chang,

Weizhen Zuo

et al.

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: unknown, P. 115907 - 115907

Published: Dec. 1, 2024

Language: Английский

Citations

0