Integrating Time Series Decomposition and Multivariable Approaches for Enhanced Cooling Energy Management

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134740 - 134740

Published: Jan. 1, 2025

Language: Английский

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Short-Term Wind Power Prediction Method Based on CEEMDAN-VMD-GRU Hybrid Model

Energies, Journal Year: 2025, Volume and Issue: 18(6), P. 1465 - 1465

Published: March 17, 2025

In order to improve wind power prediction accuracy and increase the utilization of power, this study proposes a novel complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)–variational modal (VMD)–gated recurrent unit (GRU) model. With goal extracting feature information that existed in temporal series data, CEEMDAN VMD are used divide raw data into several intrinsic function components. Furthermore, reduce computational burden enhance convergence speed, these (IMF) components integrated rebuilt via results sample entropy K-means. Lastly, ensure completeness outcomes, final synthesized through superposition all IMF The simulation indicate proposed model is superior other models robustness.

Language: Английский

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Wavelet-Based Analysis of Subsidence Patterns and High-Risk Zone Delineation in Underground Metal Mining Areas Using SBAS-InSAR

Land, Journal Year: 2025, Volume and Issue: 14(5), P. 992 - 992

Published: May 4, 2025

Underground metal mines operated using the natural caving method often result in significant surface collapses. Key parameters such as settlement magnitude, rate, extent, and influence of underground mining on deformation warrant serious attention. However, due to long operational timespan incomplete data from early collapse events, coupled with inaccessibility zones for field measurements, it is challenging obtain accurate displacement data, thereby posing difficulties follow-up research. This study employs small baseline subset InSAR (SBAS-InSAR) technology retrieve time series early-stage rates areas, compensating lack historical eliminating safety risks associated on-site measurements. The 5th percentile across all monitoring points used define severe threshold, determined be −42.1 mm/year. Continuous wavelet transform (CWT) applied calculate time-series power spectrum, allowing analysis long-term stable periodic patterns area. instantaneous change rate at each point area identified. Using 97th series, number events determined. High-incidence sudden are visualized through QGIS 3.16 heat map clustering. high-risk area, identified by integrating both patterns, accounts multiple modes. provides robust technical support management mine offers important theoretical guidance.

Language: Английский

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Machine learning for open-pit mining: a systematic review

International Journal of Mining Reclamation and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: June 20, 2024

Language: Английский

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