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

Weizhen Zuo

и другие.

Applied Mathematical Modelling, Год журнала: 2024, Номер unknown, С. 115907 - 115907

Опубликована: Дек. 1, 2024

Язык: Английский

Forecasting the electric power load based on a novel prediction model coupled with accumulative time-delay effects and periodic fluctuation characteristics DOI
Junjie Wang,

Wenyu Huang,

Yuanping Ding

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 134518 - 134518

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2

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

Xinping Xiao,

Mingyun Gao

и другие.

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122408 - 122408

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

A neural network grey model based on dynamical system characteristics and its application in predicting carbon emissions and energy consumption in China DOI

Chunyan He,

Huiming Duan, Edward Y. S. Liu

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер 266, С. 126101 - 126101

Опубликована: Дек. 9, 2024

Язык: Английский

Процитировано

3

A multivariate partial grey prediction model based on second-order traffic flow kinematics equation and its application DOI
Qiqi Zhou, Huiming Duan,

De-Rong Xie

и другие.

Journal of Computational and Applied Mathematics, Год журнала: 2025, Номер 463, С. 116505 - 116505

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

0

Review of Machine Learning Methods for Steady State Capacity and Transient Production Forecasting in Oil and Gas Reservoir DOI Creative Commons
Dongyan Fan, S.Y. Lai, Hai Sun

и другие.

Energies, Год журнала: 2025, Номер 18(4), С. 842 - 842

Опубликована: Фев. 11, 2025

Accurate oil and gas production forecasting is essential for optimizing field development operational efficiency. Steady-state capacity prediction models based on machine learning techniques, such as Linear Regression, Support Vector Machines, Random Forest, Extreme Gradient Boosting, effectively address complex nonlinear relationships through feature selection, hyperparameter tuning, hybrid integration, achieving high accuracy reliability. These maintain relative errors within acceptable limits, offering robust support reservoir management. Recent advancements in spatiotemporal modeling, Physics-Informed Neural Networks (PINNs), agent-based modeling have further enhanced transient forecasting. Spatiotemporal capture temporal dependencies spatial correlations, while PINN integrates physical laws into neural networks, improving interpretability robustness, particularly sparse or noisy data. Agent-based complements these techniques by combining measured data with numerical simulations to deliver real-time, high-precision predictions of dynamics. Despite challenges computational scalability, sensitivity, generalization across diverse reservoirs, future developments, including multi-source lightweight architectures, real-time predictive capabilities, can improve forecasting, addressing the complexities supporting sustainable resource management global energy security.

Язык: Английский

Процитировано

0

Prediction of China’s unconventional natural gas production based on grey waveform prediction model and non-homogeneous exponential discrete model DOI
Yong Xu, Yanqiu Wang, Pan Yan

и другие.

Energy Reports, Год журнала: 2025, Номер 13, С. 2829 - 2843

Опубликована: Фев. 22, 2025

Язык: Английский

Процитировано

0

A novel fractional order grey Euler model and its application in China's clean energy production prediction DOI

Zhongsen Yang,

Yong Wang, Neng Fan

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 135609 - 135609

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

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

Weizhen Zuo

и другие.

Applied Mathematical Modelling, Год журнала: 2024, Номер unknown, С. 115907 - 115907

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2