Since the mid-1990's, symbolic regression via geneticprogramming (GP) has become a core component of amulti-disciplinary approach to empirical modeling atDow Chemical. Herein we review the role of symbolicregression within an integrated empirical modelingmethodology, discuss symbolic regression system designissues, best practices and lessons learned fromindustrial application, and present future directionsfor research and application
CITATION STYLE
Kotanchek, M., Smits, G., & Kordon, A. (2003). Industrial Strength Genetic Programming. In Genetic Programming Theory and Practice (pp. 239–255). Springer US. https://doi.org/10.1007/978-1-4419-8983-3_15
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