Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm
Abstract
:1. Introduction
2. Establishment of Model
3. Streamer Array Geometry Inversion Using an Improved PSO Algorithm
3.1. Basic Particle Swarm Optimization (PSO) Algorithm
3.2. Improved Inversion Strategy Based on the PSO Algorithm
3.2.1. Improved PSO Algorithm
3.2.2. Objective Function and Methods
4. Results
4.1. Comparative Analysis of Practical Data Inversion Using Different Strategies
4.2. Analysis of the Results before and after Improvement
4.3. Performances of Different Strategies Excluding Error Effects
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Nomenclature
Decision parameters | ||||
Symbol | Definition | Size | Value | |
D | Dimensionality of the search space | 1 × 1 | 51 | |
Position vector of particle | 1 × 51 | |||
Velocity vector of particle | 1 × 51 | |||
Personal best vector of particle | 1 × 51 | |||
Global best vector | 1 × 51 | |||
Inertia weight | 1 × 1 | |||
Personal learning factor | 1 × 1 | 1 | ||
Global learning factor | 1 × 1 | 1 | ||
, | Random vectors within [0, 1] | 1 × 1 | ||
Inertia weight decay factor | 1 × 1 | 0.01 | ||
Perturbation strength adjustment factor | 1 × 1 | 0.05 | ||
Variance decay factor | 1 × 1 | 0.005 | ||
Model parameters | ||||
Symbol | Definition | Size | Value | Unit |
X | Excitation spacing interval | 1 × 1 | 6.25 | m |
Lateral distance from source to streamer | 1 × 1 | 2 | m | |
Vertical distance from source to streamer | 1 × 1 | 0.6 | m | |
Hydrophone interval | 1 × 1 | 3.125 | m | |
Depth of source for shot | 1 × 1 | m | ||
Pitch angle for hydrophone | 1 × 1 | rad | ||
Abscissa for hydrophone for shot | 1 × 1 | m | ||
Ordinate for hydrophone for shot | 1 × 1 | m | ||
v | Sound velocity of seawater | 1 × 1 | 1485 | m/s |
Real travel time vector of direct wave | 1 × 48 | ms | ||
Real travel time vector of seafloor-reflected wave | 1 × 48 | ms | ||
Calculated travel time vector for direct wave | 1 × 48 | ms | ||
Calculated travel time vector for seafloor-reflected wave | 1 × 48 | ms | ||
Model travel time vector of direct wave | 1 × 48 | ms | ||
Model travel time vector of seafloor-reflected wave | 1 × 48 | ms |
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Strategy | Maximum Iteration | Initialization of Particle Vector | Inertia Weight Generation Strategy | Average Best Fitness Value |
---|---|---|---|---|
1. PSO | 100 | zeros (1,51) | 1 | 57.963654 |
2. PSO-G | 100 | zeros (1,51) | Formula (3) | 4.514059 |
3. PSO-C | 100 | last (1,51) | 1 | 23.299226 |
4. PSO-CG | 100 | last (1,51) | Formula (3) | 4.126673 |
Strategy | Maximum Iteration | Initialization of Particle Vector | Inertia Weight Generation Strategy | Average Time Cost (s) | Average Best Fitness Value | Position Error (m) (Per Hydrophone) |
---|---|---|---|---|---|---|
1. PSO | 100 | zeros (1,51) | 1 | 2.41898 | 38.97512 | 1.21158 |
2. PSO-G | 100 | zeros (1,51) | Formula (3) | 2.43994 | 0.32962 | 0.10353 |
3. PSO-C | 100 | last (1,51) | 1 | 2.59914 | 9.38700 | 0.59843 |
4. PSO-CG | 100 | last (1,51) | Formula (3) | 2.48249 | 0.04001 | 0.03528 |
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Luo, X.; Liu, K.; Pei, Y.; Liu, C.; Li, X.; Xiao, Y. Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm. J. Mar. Sci. Eng. 2024, 12, 282. https://doi.org/10.3390/jmse12020282
Luo X, Liu K, Pei Y, Liu C, Li X, Xiao Y. Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm. Journal of Marine Science and Engineering. 2024; 12(2):282. https://doi.org/10.3390/jmse12020282
Chicago/Turabian StyleLuo, Xiaohu, Kai Liu, Yanliang Pei, Chenguang Liu, Xishuang Li, and Yibao Xiao. 2024. "Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm" Journal of Marine Science and Engineering 12, no. 2: 282. https://doi.org/10.3390/jmse12020282
APA StyleLuo, X., Liu, K., Pei, Y., Liu, C., Li, X., & Xiao, Y. (2024). Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm. Journal of Marine Science and Engineering, 12(2), 282. https://doi.org/10.3390/jmse12020282