Abstract
Since the mid-1990’s, symbolic regression via genetic programming (GP) has become a core component of a multi-disciplinary approach to empirical modeling at Dow Chemical. Herein we review the role of symbolic regression within an integrated empirical modeling methodology, discuss symbolic regression system design issues, best practices and lessons learned from industrial application, and present future directions for research and application
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References
Banzhaf, W., Nordin, P., Keller, R. and Francone, F. (1998). Genetic Programming - An Introduction. Morgan Kaufmann, San Francisco, CA.
Castillo, F. A., Marshall, K., Green, J. and Kordon, A. K. (2002). Symbolic Regression in Design of Experiments: A Case Study with Linearizing Transformations. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), W. B. Langdon, et al. (Eds. ), pp. 1043–1048. New York: Morgan Kaufmann.
Hastie, T., Tibshirani, R. and Friedman, J. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer-Verlag.
Jacob, C. (2001). Illustrating Evolutionary Computation with Mathematica. San Francisco: Morgan Kaufmann.
Jordaan, E. Maria. (2002). Development of Robust Inferential Sensors: Industrial Application of Support Vector Machines for Regression. Eindhoven: Universiteitsdrukkerij TU Eindhoven.
Kordon, A. K., Pham, H. T., Bosnyak, C. P. and Kotanchek, M. E. (2002). Accelerating Indus-trial Fundamental Model Building with Symbolic Regression: A Case Study with Structure- Property Relationships. In GECCO 2002: Presentations in the Evolutionary Compution in Industry Track, D. Davis and R. Roy (Eds. ), pp. 111–116. New York: GECCO 2002 Conference.
Kordon, A. K. and Smits, G. F. (2001). Soft Sensor Development using Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), L. Spector, et al. (Eds. ), pp. 1346–1351. New York, Morgan Kaufmann.
Kotanchek, M. E., et al. (2002). Evolutionary Computing in Dow Chemical. In GECCO 2002 Presentations in the Evolutionary Computation in Industry Track, D. Davis and R. Roy (Eds. ), pp. 101–110. New York: GECCO 2002 Conference.
Kotanchek, M. E., (2003). Industrial Strength Symbolic Regression: Evolving Empirical Models from Industrial Data. 2003 Mathematica Developers Conference, Champaign, IL: Presentation.
Mercure, P. Kip., Smits, G. F. and Kordon, A. K. (2001). Empirical Emulators for First Principle Models. Fall 2001 AIChE Meeting. Reno: Presentation.
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Kotanchek, M., Smits, G., Kordon, A. (2003). Industrial Strength Genetic Programming. In: Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice. Genetic Programming Series, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8983-3_15
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DOI: https://doi.org/10.1007/978-1-4419-8983-3_15
Publisher Name: Springer, Boston, MA
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