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Visualizing the Results of the Calibration of the Distributed Hydrological Model Iber+ with the Surrogate-Assisted Evolutionary Algorithm
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| Type: | Resource | |
| Storage: | The size of this resource is 3.6 MB | |
| Created: | Jul 25, 2023 at 12:38 p.m. | |
| Last updated: | Jul 28, 2023 at 5:03 p.m. (Metadata update) | |
| Published date: | Jul 28, 2023 at 5:03 p.m. | |
| DOI: | 10.4211/hs.1a7d73ae3ac044969740f985b56d031c | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 502 |
| Downloads: | 8 |
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Abstract
This data represents outcomes from experiments focused on optimizing a distributed hydrological model via a Surrogate-Assisted Evolutionary Algorithm (SAEA). Two scripts perform data analysis, visualization, and strategy comparison. The first script imports pertinent datasets, visualizes the model's performance, and applies the Generalized Likelihood Uncertainty Estimation (GLUE) methodology to create a confidence band for predictions. The second script manages data for multiple generations and compares Monte Carlo (MC) and Evolutionary Algorithm with Surrogate Modeling (EA-SM) strategies, visualized in a scatter plot. Together, these scripts provide comprehensive insights into the model's performance, efficiency, and potential enhancements.
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Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| Xunta de Galicia | Pre-doctoral fellowship program Axudas de apoio á etapa predoutoral 2019 | ED481A-2019/014 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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