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Optimal polynomial regression models by using a genetic algorithm
Department of Mechanical Engineering, University of Jönköping, Jönköping, Sweden.
Department of Mechanical Engineering, University of Jönköping, Jönköping, Sweden.ORCID-id: 0000-0001-6821-5727
Department of Mechanical Engineering, University of Jönköping, Jönköping, Sweden.
2011 (engelsk)Inngår i: Proceedings of the second International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering / [ed] Yiannis Tsompanakis; B.H.V. Topping, Kippen, Scotland: Civil-Comp Proceedings , 2011Konferansepaper, Publicerat paper (Fagfellevurdert)
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Text
Abstract [en]

In this paper a polynomial regression model where the constituents of are of arbitrary order is proposed. A genetic algorithm is used to find the optimal terms to be included in the so-called optimal polynomial regression model . The objective for the genetic algorithm is to minimize the sum of squared errors of the predicted responses. In practice the genetic algorithm generates an optimal set of exponents of the design variables in a polynomial regression model. Several example problems are presented to show the performance and accuracy of the optimal polynomial regression model. Results show a greatly improved performance for optimal polynomial regression models compared to traditional regression models.

sted, utgiver, år, opplag, sider
Kippen, Scotland: Civil-Comp Proceedings , 2011.
Serie
Civil-Comp Proceedings, ISSN 1759-3433 ; 97
Emneord [en]
Design of experiments; Genetic algorithm; Metamodel; Polynomial; Regression model; Surrogate model
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Forskningsprogram
Maskinteknik
Identifikatorer
URN: urn:nbn:se:oru:diva-48261DOI: 10.4203/ccp.97.39Scopus ID: 2-s2.0-84894135229ISBN: 9781905088492 (tryckt)ISBN: 9781905088485 (tryckt)OAI: oai:DiVA.org:oru-48261DiVA, id: diva2:904508
Konferanse
2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering (CSC 2011), Chania, Crete, Greece, September 6-9, 2011
Tilgjengelig fra: 2012-01-26 Laget: 2016-02-15 Sist oppdatert: 2018-05-07bibliografisk kontrollert

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