Application of Particle Swarm Optimization for Auto-Tuning of the Urban Flood Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Outline of the Urban Flood Model
2.2. Description of the Case Study
2.3. Sensitivity Analysis
2.4. Setup of PSO for Auto-Tuning of the Urban Flood Model
2.5. Application of PSO to the Case Study Site
3. Results and Discussions
3.1. Model Sensitivity to Manning’s Roughness
3.2. Model Sensitivity to the Coefficient, α
3.3. Application of the Present PSO-Based Auto-Tuning System
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Case | α (m) | ||
---|---|---|---|
0 | 0.025 | 0.013 | 5 |
A1 | 0.25 | 0.013 | 5 |
A2 | 0.0025 | 0.013 | 5 |
A3 | 0.025 | 0.13 | 5 |
A4 | 0.25 | 0.0013 | 5 |
A5 | 0.25 | 0.13 | 5 |
B1 | 0.025 | 0.013 | 0.05 |
B2 | 0.025 | 0.013 | 0.5 |
B3 | 0.025 | 0.013 | 50 |
B4 | 0.025 | 0.013 | 500 |
Case | NSE | KGE | RMSE (m) | NRMSE |
---|---|---|---|---|
case 0 | 0.55 | −0.70 | 0.36 | 0.23 |
after tuning | 0.69 | 0.65 | 0.29 | 0.19 |
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Jiang, L.; Tajima, Y.; Wu, L. Application of Particle Swarm Optimization for Auto-Tuning of the Urban Flood Model. Water 2022, 14, 2819. https://doi.org/10.3390/w14182819
Jiang L, Tajima Y, Wu L. Application of Particle Swarm Optimization for Auto-Tuning of the Urban Flood Model. Water. 2022; 14(18):2819. https://doi.org/10.3390/w14182819
Chicago/Turabian StyleJiang, Lechuan, Yoshimitsu Tajima, and Lianhui Wu. 2022. "Application of Particle Swarm Optimization for Auto-Tuning of the Urban Flood Model" Water 14, no. 18: 2819. https://doi.org/10.3390/w14182819