Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation

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发表日期：

2024年

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Christian Haider,
Fabricio Olivetti de Franca,
Bogdan Burlacu,
Florian Bachinger,
Gabriel Kronberger,
Michael Affenzeller

摘要

We present different approaches for including knowledge in data-based modeling. For this, we utilize the model representation of symbolic regression (SR), which represents the models as short interpretable mathematical formulas. The integration of knowledge into symbolic regressionSymbolic regression via shape constraints is discussed alongside three real-world applications: modeling magnetization curves, modeling twin-screw extruders and model-based data validation.