A multi-factor combined traffic flow prediction model with secondary decomposition and improved entropy weight method

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124424 - 124424

Published: June 18, 2024

Language: Английский

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Research on feature extraction method for underwater acoustic signal using secondary decomposition

Ocean Engineering, Journal Year: 2024, Volume and Issue: 306, P. 117974 - 117974

Published: May 8, 2024

Language: Английский

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Adaptive denoising model for ship-radiated noise based on dynamic weighted filtering

Measurement, Journal Year: 2024, Volume and Issue: 236, P. 115042 - 115042

Published: June 2, 2024

Language: Английский

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Energy fluctuation pattern recognition coupled with decomposition-integration: A novel ocean tidal energy forecasting system

Measurement, Journal Year: 2024, Volume and Issue: 238, P. 115374 - 115374

Published: July 23, 2024

Language: Английский

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A method for accurate prediction of photovoltaic power based on multi-objective optimization and data integration strategy

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: 136, P. 115643 - 115643

Published: Aug. 17, 2024

Language: Английский

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A generalized fault diagnosis framework for rotating machinery based on phase entropy

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: unknown, P. 110745 - 110745

Published: Dec. 1, 2024

Language: Английский

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Short-term offshore wind speed forecasting approach based on multi-stage decomposition and deep residual network with self-attention

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 146, P. 110313 - 110313

Published: Feb. 19, 2025

Language: Английский

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Predicting water demand for spraying operations in dry bulk ports: A hybrid approach based on data decomposition and deep learning

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103313 - 103313

Published: April 2, 2025

Language: Английский

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A new denoising method of ship-radiated noise: Improved variational mode decomposition coupled with fractional order entropy double threshold criterion

Measurement Science and Technology, Journal Year: 2024, Volume and Issue: 35(12), P. 126112 - 126112

Published: Aug. 2, 2024

Abstract Ship-radiated noise (SRN) contains abundant ship characteristic information. The detection and analysis of SRN is very important for target recognition, positioning tracking. However, complex ocean easily interferes with the propagation in water. To achieve a preferable denoising effect, new method proposed. First, decomposed by an improved variational mode decomposition (DVMD) dung beetle optimizer, complexity each intrinsic function after measured fractional order refined composite multiscale fluctuation dispersion entropy (FRCMFDE). Second, distribution characteristics are analyzed, different adaptive division methods used to determine modes, i.e. it divides all modes into clean mildly noisy moderately highly modes. Then, locally weighted scatterplot smoothing dual-tree wavelet transform (IDTCWT) denoise respectively. Finally, denoised obtained reconstructing two groups proposed Rossler, Chen Lorenz signals, signal-to-noise ratio (SNR) 13.0785, 11.9390 12.3775 dB, Compared DVMD-FRCMFDE, DVMD-FRCMFDE-wavelet soft threshold ( WSTD) DVMD-FRCMFDE-IDTCWT, SNR increased 48%, 45.93% 38.76%, respectively, root mean square error 46.55%, 42.76% 30.04%, applied four types SRN. Based on these findings, enhances clarity smoothness phase space attractor, effectively suppresses marine environmental SRN, which provides solid groundwork subsequent processing

Language: Английский

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RegStack machine learning model for accurate prediction of tidal stream turbine performance and biofouling

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127766 - 127766

Published: April 1, 2025

Language: Английский

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