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Copy file name to clipboardExpand all lines: docs/userguide/model_calibration.md
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@@ -32,7 +32,7 @@ the calibration interface offers flexible options for optimizing model parameter
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- Automatic saving of optimization history for each generation, enabling analysis of optimization progress, convergence trends, performance indicators, and visualization.
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The interface provides a [`Calibration`](https://swat-model.github.io/pySWATPlus/api/model_calibration/) class that must be initialized with the required parameters.
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The interface provides a [`Calibration`](https://swat-model.github.io/pySWATPlus/api/calibration/) class that must be initialized with the required parameters.
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This class includes the `parameter_optimization` method, which performs parameter optimization using multi-objective algorithms, evolutionary strategies, and parallel computation.
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The following code provides an example of optimizing flow discharge for both daily and monthly time-series data using multi-objective evolutionary computation.
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