Multiscale Fractures Characterization Based on Ant Colony Optimization and Two-Dimensional Variational Mode Decomposition

2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jinwei Zhang ◽  
Handong Huang ◽  
Tao Liu ◽  
Chen Zhang
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Two Dimensional ◽  
Variational Mode Decomposition ◽  
Mode Decomposition

scholarly journals Two-Dimensional Compact Variational Mode Decomposition

2017 ◽  
Vol 58 (2) ◽  
pp. 294-320 ◽  
Author(s):  
Dominique Zosso ◽  
Konstantin Dragomiretskiy ◽  
Andrea L. Bertozzi ◽  
Paul S. Weiss
Keyword(s):  
Two Dimensional ◽  
Variational Mode Decomposition ◽  
Mode Decomposition

Application of improved variational mode decomposition method based on two-dimensional sparrow search algorithm in natural gas pipeline leakage signal denoising

2021 ◽  
pp. 014233122110636
Author(s):  
Dongmei Wang ◽  
Lijuan Zhu ◽  
Jikang Yue ◽  
Jingyi Lu ◽  
Gongfa Li
Keyword(s):  
Search Algorithm ◽  
Signal To Noise Ratio ◽  
Decomposition Algorithm ◽  
Signal Denoising ◽  
Two Dimensional ◽  
Variational Mode Decomposition ◽  
Denoising Method ◽  
Mode Decomposition ◽  
Penalty Factor ◽  
Whale Optimization

To eliminate noise interference in pipeline leakage detection, a signal denoising method based on an improved variational mode decomposition algorithm is proposed. This work adopts a standard variational mode decomposition algorithm with decomposition level K and the penalty factor α. The improvements consist of using a two-dimensional sparrow search algorithm to find K and α. To verify the superiority of the sparrow search algorithm to find K and α, it is compared with three earlier studies. These studies used the firefly algorithm, particle swarm optimization, and whale optimization algorithm to perform the optimization. The main result of this study is to demonstrate that the variational mode decomposition improved by sparrow search algorithm gives a much improved signal-to-noise ratio compared to the other methods. In all other respects, the results are comparable.

Ant colony optimization for the two-dimensional loading vehicle routing problem

2009 ◽  
Vol 36 (3) ◽  
pp. 655-673 ◽  
Author(s):  
Guenther Fuellerer ◽  
Karl F. Doerner ◽  
Richard F. Hartl ◽  
Manuel Iori
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Two Dimensional ◽  
Routing Problem

scholarly journals Adaptive Vibrarthographic Signal Denoising via Ant Colony Optimization Using Dynamic Denoising Filter Parameters

2021 ◽  
Vol 12 (1) ◽  
pp. 01-15
Author(s):  
Rui Gong ◽  
Kazunori Hase ◽  
Hajime Ohtsu ◽  
Susumu Ota
Keyword(s):  
Ant Colony Optimization ◽  
Signal To Noise Ratio ◽  
Ensemble Empirical Mode Decomposition ◽  
Ant Colony ◽  
Denoising Method ◽  
Mode Decomposition ◽  
Snr Improvement ◽  
Mean Square Difference ◽  
Dynamic Filter

This study proposes an ant colony optimization (ACO) denoising method with dynamic filter parameters. The proposed method is developed based on ensemble empirical mode decomposition (EEMD), and aims to improve the quality of vibrarthographic (VAG) signals. It mixes the original VAG signals with different white noise amplitudes, and adopts a hybrid technology that combines EEMD with a Savitzky-Golay (SG) filter containing the dynamic parameters optimized by ACO. The results show that the proposed method provides a higher peak signal-to-noise ratio (PSNR) and a smaller root-mean-square difference than the regular methods. The SNR improvement for the VAG signals of normal knees can reach 13 dB while maintaining the original signal structure, and the SNR improvement for the VAG signals of abnormal knees can reach 20 dB. The method proposed in this study can improve the quality of nonstationary VAG signals.

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