Automatic discovery of the regression model by the means of grammatical and differential evolution

Jiří Lýsek and Jiří Šťastný
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Jiří Lýsek: Department of Informatics, Faculty of Business and Economics, Mendel University in Brno, Brno, Czech Republic
Jiří Šťastný: Department of Informatics, Faculty of Business and Economics, Mendel University in Brno, Brno, Czech Republic

Agricultural Economics, 2014, vol. 60, issue 12, 546-552

Abstract: In the contribution, there is discussed the usage of the method based on the grammatical and differential evolution for the automatic discovery of regression models for discrete datasets. The combination of these two methods enables the process to find the precise structure of the mathematical model and values for the model constants separately. The used method is described and tested on the selected regression examples. The results are reported and the obtained mathematical models are presented. The advantages of the selected approach are described and compared to the classical methods.

Keywords: context-free grammar; evolutionary methods; genetic algorithm; sum of squared error (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:60:y:2014:i:12:id:160-2014-agricecon

DOI: 10.17221/160/2014-AGRICECON

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