A clustering fractional-order grey model in short-term electrical load forecasting

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 20, 2025

Short-term electrical load series forecast plays an essential role in energy demand management, however power consumption data are non-stationary, nonlinear and multi-dimensional series, leaving prediction a difficult task. Recently, fractional- order partial differential equations attracting attention as they have been successfully utilized to describe behaviors complex systems grids. In this paper, clustering fractional predictive model called C-FGM is introduced for short-term missions. The novelty of the that it initiates parameter α accumulative weather trends multiple sub-series, also assigned fractional-order equation depict previous series. Hyper parameters these then sent global optimization algorithm reduce errors. Simulation results on two electricity datasets demonstrated our can learn from hyper inside produce values efficiently. Com- pared with contemporary models such LSTM Transformer, clearly achieved higher accuracy (MAPE 1.97 4.67%, outperforms whose average MAPE 4.34% Transformer 5.42%). This satisfactory performance suggests data-driven be used effective tool real time forecasting

Language: Английский

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Dynamic prediction and quantitative assessment of carbon emissions from animal husbandry: A case study of inner mongolia autonomous region, China

Journal of Environmental Quality, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Abstract Climate change, driven by greenhouse gas emissions, has emerged as a pressing global ecological and environmental challenge. Our study is dedicated to exploring the various factors influencing emissions from animal husbandry predicting their future trends. To this end, we have analyzed data China's Inner Mongolia Autonomous Region spanning 1978 2022, aiming estimate carbon associated with in region. Furthermore, constructed an SA‐STIRPAT model grounded scenario analysis forecast timing of peak. findings reveal several notable From 2001 region followed pattern “rapid growth, smooth fluctuations, then gradual recovery.” Notably, 2019, reached peak contribution accounting for 8.34% national total. Ruminants, including cattle, sheep, camels, were identified primary emitters, responsible 91.6% total emissions. Additionally, our indicates that such production efficiency, industrial structure, economic level, population structure positively impact while size negatively affects husbandry's footprint. predicts under both low‐carbon benchmark scenarios, are expected decline after 2030. However, high‐carbon scenario, anticipated 2040. In conclusion, achieve Mongolia's “dual carbon” goals, it imperative implement effective control measures, enhance elevate level urbanization, optimize structure.

Language: Английский

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Novel disctete grey Bernoulli seasonal model with a time powter term for predicting monthly carbon dioxide emissions in the United States

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

Published: Jan. 3, 2025

This study proposes a more efficient discrete grey prediction model to describe the seasonalvariation trends of carbon dioxide emissions. The setting bernoulli parameter and time powerterm in new ensures that can capture trend nonlinear changesin sequence. At same time, inclusion dummy variables allows for direct simulationof seasonal fluctuations emissions without need additional treatment theseasonality optimal search model’s hyperparameters is achieved using MPA algorithm. constructed applied monthly U.S. datafrom January 2003 December 2022, total 240 months. trained on 216 months 2020, data from 2021 2022 usedfor prediction, which then compared with actual values. results show proposed modelexhibits higher forecasting performance SARIMA other models. Therefore, this methodcan effectively simulate variation emissions, providing valuablereference information relevant departments formulate effective policies.

Language: Английский

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An innovative prediction algorithm based on grey modeling theory and the marine predators algorithm for short-term carbon dioxide emissions in China

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 137, P. 109066 - 109066

Published: Aug. 11, 2024

Language: Английский

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