Shih-Lin Lin^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1365-1382, 2025, DOI:10.32604/cmc.2025.067764 - 29 August 2025

Abstract This paper proposes an integrated multi-stage framework to enhance frequency modulated continuous wave (FMCW) automotive radar performance under high noise and interference. The four-stage pipeline is applied consecutively: (i) an improved independent component analysis (ICA) blindly separates the two-channel echoes, isolating target and interference components; (ii) a recursive least-squares (RLS) filter compensates amplitude- and phase-mismatches, restoring signal fidelity; (iii) variational mode decomposition (VMD) followed by the Hilbert-Huang Transform (HHT) extracts noise-free intrinsic mode functions (IMFs) and sharpens their time-frequency signatures; and (iv) HHT-based beat-frequency estimation reconstructs a clean echo and delivers accurate range information. Finally, More >

Guangfei Jia^*, Jinqiu Yang, Hanwen Liang

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 1057-1072, 2025, DOI:10.32604/sdhm.2025.061805 - 30 June 2025

Abstract Considering the noise problem of the acquisition signals from mechanical transmission systems, a novel denoising method is proposed that combines Variational Mode Decomposition (VMD) with wavelet thresholding. The key innovation of this method lies in the optimization of VMD parameters K and using the improved Horned Lizard Optimization Algorithm (IHLOA). An inertia weight parameter is introduced into the random walk strategy of HLOA, and the related formula is improved. The acquisition signal can be adaptively decomposed into some Intrinsic Mode Functions (IMFs), and the high-noise IMFs are identified based on a correlation coefficient-variance method. Further noise… More > Graphic Abstract

Zhebin Sun¹, Wei Wang¹, Mingxuan Du², Tao Liang¹, Yang Liu¹, Hailong Fan³, Cuiping Li², Xingxu Zhu², Junhui Li^2,*

Energy Engineering, Vol.122, No.6, pp. 2155-2175, 2025, DOI:10.32604/ee.2025.062218 - 29 May 2025

Abstract Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation. This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition (VMD) and Channel Attention Mechanism. First, Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical power. Second, the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition (VMD). Finally, the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM… More >

Yingnan Zhao^*, Yuyuan Ruan, Zhen Peng

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 549-566, 2024, DOI:10.32604/cmc.2024.056240 - 15 October 2024

Abstract As the penetration ratio of wind power in active distribution networks continues to increase, the system exhibits some characteristics such as randomness and volatility. Fast and accurate short-term wind power prediction is essential for algorithms like scheduling and optimization control. Based on the spatio-temporal features of Numerical Weather Prediction (NWP) data, it proposes the WVMD_DSN (Whale Optimization Algorithm, Variational Mode Decomposition, Dual Stream Network) model. The model first applies Pearson correlation coefficient (PCC) to choose some NWP features with strong correlation to wind power to form the feature set. Then, it decomposes the feature set More >

Dijun Rao^1,2,3,4, Min Huang^1,2,3,5, Xiuzhi Shi⁴, Zhi Yu^6,*, Zhengxiang He⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 187-217, 2024, DOI:10.32604/cmes.2024.051402 - 20 August 2024

Abstract The denoising of microseismic signals is a prerequisite for subsequent analysis and research. In this research, a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm (BWOA) optimized Variational Mode Decomposition (VMD) joint Wavelet Threshold Denoising (WTD) algorithm (BVW) is proposed. The BVW algorithm integrates VMD and WTD, both of which are optimized by BWOA. Specifically, this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited Intrinsic Mode Functions (BLIMFs). Subsequently, these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold… More >

Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374 - 30 April 2024

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on More >

Xiangqun Li^1,*, Jiawen Liang², Jinyu Zhu², Shengping Shi², Fangyu Ding², Jianpeng Sun², Bo Liu²

Energy Engineering, Vol.121, No.1, pp. 203-219, 2024, DOI:10.32604/ee.2023.029295 - 27 December 2023

Abstract To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis, this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition (VMD), fuzzy entropy (FE) and fuzzy clustering (FC). Firstly, based on the OTDR curve data collected in the field, VMD is used to extract the different modal components (IMF) of the original signal and calculate the fuzzy entropy (FE) values of different components to characterize the subtle differences between them. The fuzzy entropy of each curve is used More >

Yinghua Song^1,2, Hairong Lyu^1,2, Wei Zhang^1,2,*

Journal on Big Data, Vol.5, pp. 19-40, 2023, DOI:10.32604/jbd.2023.038249 - 05 October 2023

Abstract A precise and timely forecast of short-term rail transit passenger flow provides data support for traffic management and operation, assisting rail operators in efficiently allocating resources and timely relieving pressure on passenger safety and operation. First, the passenger flow sequence models in the study are broken down using VMD for noise reduction. The objective environment features are then added to the characteristic factors that affect the passenger flow. The target station serves as an additional spatial feature and is mined concurrently using the KNN algorithm. It is shown that the hybrid model VMD-CLSMT has a More >

Shoutao Li^1,2,*, Ruyi Qu¹, Yu Zhang¹, Dingli Yu³

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2809-2823, 2023, DOI:10.32604/iasc.2023.036999 - 11 September 2023

Abstract Freezing of Gait (FOG) is the most common and disabling gait disorder in patients with Parkinson’s Disease (PD), which seriously affects the life quality and social function of patients. This paper proposes a FOG recognition method based on the Variational Mode Decomposition (VMD). Firstly, VMD instead of the traditional time-frequency analysis method to complete adaptive decomposition to the FOG signal. Secondly, to improve the accuracy and speed of the recognition algorithm, use the CART model as the base classifier and perform the feature dimension reduction. Then use the RUSBoost ensemble algorithm to solve the problem… More >

Qiansheng Fang, Haojie Wang, Chenlei Xie^*, Jie Chen

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1237-1250, 2023, DOI:10.32604/cmes.2022.021131 - 31 August 2022

Abstract At present, the leakage rate of the water distribution network in China is still high, and the waste of water resources caused by water distribution network leakage is quite serious every year. Therefore, the location of pipeline leakage is of great significance for saving water resources and reducing economic losses. Acoustic emission technology is the most widely used pipeline leak location technology. The traditional non-stationary random signal de-noising method mainly relies on the estimation of noise parameters, ignoring periodic noise and components unrelated to pipeline leakage. Aiming at the above problems, this paper proposes a… More >