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

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

doi:10.1007/978-981-99-8413-8_12

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

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

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

Abstract

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.

Original language	Undefined/Unknown
Title of host publication	Genetic Programming Theory and Practice XX
Editors	Stephan Winkler, Leonardo Trujillo, Charles Ofria, Ting Hu
Place of Publication	Singapore
Publisher	Springer Nature Singapore
Pages	225-240
Number of pages	16
ISBN (Print)	978-981-99-8413-8
DOIs	https://doi.org/10.1007/978-981-99-8413-8_12
Publication status	Published - 2024

Access to Document

10.1007/978-981-99-8413-8_12

Cite this

Haider, C., de Franca, F. O., Burlacu, B., Bachinger, F., Kronberger, G., & Affenzeller, M. (2024). Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. In S. Winkler, L. Trujillo, C. Ofria, & T. Hu (Eds.), Genetic Programming Theory and Practice XX (pp. 225-240). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-8413-8_12

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Haider, C, de Franca, FO, Burlacu, B , Bachinger, F , Kronberger, G & Affenzeller, M 2024, Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. in S Winkler, L Trujillo, C Ofria & T Hu (eds), Genetic Programming Theory and Practice XX. Springer Nature Singapore, Singapore, pp. 225-240. https://doi.org/10.1007/978-981-99-8413-8_12

Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. / Haider, Christian; de Franca, Fabricio Olivetti; Burlacu, Bogdan et al.
Genetic Programming Theory and Practice XX. ed. / Stephan Winkler; Leonardo Trujillo; Charles Ofria; Ting Hu. Singapore: Springer Nature Singapore, 2024. p. 225-240.

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

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Haider C, de Franca FO, Burlacu B , Bachinger F , Kronberger G , Affenzeller M. Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation. In Winkler S, Trujillo L, Ofria C, Hu T, editors, Genetic Programming Theory and Practice XX. Singapore: Springer Nature Singapore. 2024. p. 225-240 doi: 10.1007/978-981-99-8413-8_12