Meta-Modeling by Symbolic Regression and Pareto Simulated Annealing
AbstractThe subject of this paper is a new approach to Symbolic Regression.Other publications on Symbolic Regression use Genetic Programming.This paper describes an alternative method based on Pareto Simulated Annealing.Our method is based on linear regression for the estimation of constants.Interval arithmetic is applied to ensure the consistency of a model.In order to prevent over-fitting, we merit a model not only on predictions in the data points, but also on the complexity of a model.For the complexity we introduce a new measure.We compare our new method with the Kriging meta-model and against a Symbolic Regression meta-model based on Genetic Programming.We conclude that Pareto Simulated Annealing based Symbolic Regression is very competitive compared to the other meta-model approaches
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2006-15.
Date of creation: 2006
Date of revision:
Contact details of provider:
Web page: http://center.uvt.nl
approximation; meta-modeling; pareto simulated annealing; symbolic regression;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-04-01 (All new papers)
- NEP-CMP-2006-04-01 (Computational Economics)
- NEP-ECM-2006-04-01 (Econometrics)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Siem, A.Y.D., 2008. "Property Preservation and Quality Measures in Meta-Models," Open Access publications from Tilburg University urn:nbn:nl:ui:12-364657, Tilburg University.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Richard Broekman).
If references are entirely missing, you can add them using this form.