Nonlinear Dynamics, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 10, 2024
Language: Английский
Nonlinear Dynamics, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 10, 2024
Language: Английский
Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127649 - 127649
Published: April 1, 2025
Language: Английский
Citations
0Measurement 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
Citations
2Ocean Engineering, Journal Year: 2024, Volume and Issue: 313, P. 119550 - 119550
Published: Oct. 23, 2024
Language: Английский
Citations
2Sensors, Journal Year: 2024, Volume and Issue: 24(21), P. 7045 - 7045
Published: Oct. 31, 2024
Mixed non-motorized traffic is largely unaffected by motor vehicle congestion, offering high accessibility and convenience, thus serving as a primary mode of "last-mile" transportation in urban areas. To advance stochastic capacity estimation methods provide reliable assessments roadway capacity, this study proposes model based on power spectral analysis. The treats discrete flow data time-series signal employs parameter to fit patterns. Initially, UAVs video cameras are used capture videos mixed flow. were processed with an image detection algorithm the YOLO convolutional neural network tracking using DeepSORT multi-target model, extracting flow, density, speed, rider characteristics. Then, autocorrelation partial functions employed distinguish among four classical models. parameters optimized minimizing AIC information criterion identify optimal fit. fitted parametric models analyzed transforming them from time domain frequency domain, spectrum then calculated. experimental results show that yields pure EV 2060-3297 bikes/(h·m) bicycle 1538-2460 bikes/(h·m). density-flow calculates 2349-2897 1753-2173 minimal difference between these estimates validates effectiveness proposed model. These findings hold practical significance addressing road congestion.
Language: Английский
Citations
2Ocean Engineering, Journal Year: 2024, Volume and Issue: 312, P. 119300 - 119300
Published: Sept. 24, 2024
Language: Английский
Citations
1Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 143680 - 143680
Published: Sept. 1, 2024
Language: Английский
Citations
0Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 143730 - 143730
Published: Sept. 1, 2024
Language: Английский
Citations
0Nonlinear Dynamics, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 10, 2024
Language: Английский
Citations
0