Models set pre-processing for genetic programming based evolvement of models of models

Mariia Semenkina; Bogdan Burlacu; Michael Affenzeller; Erik Pitzer

doi:10.1088/1757-899X/734/1/012108

Models set pre-processing for genetic programming based evolvement of models of models

Mariia Semenkina, Bogdan Burlacu, Michael Affenzeller, Erik Pitzer

Research Center Hagenberg

Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Begutachtung

1 Zitat (Scopus)

Abstract

We describe in this paper an extension of standard Genetic Programming where the terminal set of the algorithm is expanded with a set of basic models generated offline using a deterministic approach. The new algorithm called EMM-GP (Genetic Programming based Evolvement of Models of Models) uses a specialized mutation operator to sample this set during the recombination phase in order to create models that reuse valuable building blocks. In this work, a preprocessing of model set by means of clustering is considered.

Originalsprache	Englisch
Aufsatznummer	012108
Fachzeitschrift	IOP Conference Series: Materials Science and Engineering
Jahrgang	734
Ausgabenummer	1
DOIs	https://doi.org/10.1088/1757-899X/734/1/012108
Publikationsstatus	Veröffentlicht - 29 Jän. 2020
Veranstaltung	2nd International Scientific Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering, MIST: Aerospace 2019 - Krasnoyarsk, Russland Dauer: 18 Nov. 2019 → 21 Nov. 2019

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10.1088/1757-899X/734/1/012108

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author = "Mariia Semenkina and Bogdan Burlacu and Michael Affenzeller and Erik Pitzer",

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AU - Semenkina, Mariia

AU - Burlacu, Bogdan

AU - Affenzeller, Michael

AU - Pitzer, Erik

PY - 2020/1/29

Y1 - 2020/1/29

N2 - We describe in this paper an extension of standard Genetic Programming where the terminal set of the algorithm is expanded with a set of basic models generated offline using a deterministic approach. The new algorithm called EMM-GP (Genetic Programming based Evolvement of Models of Models) uses a specialized mutation operator to sample this set during the recombination phase in order to create models that reuse valuable building blocks. In this work, a preprocessing of model set by means of clustering is considered.

AB - We describe in this paper an extension of standard Genetic Programming where the terminal set of the algorithm is expanded with a set of basic models generated offline using a deterministic approach. The new algorithm called EMM-GP (Genetic Programming based Evolvement of Models of Models) uses a specialized mutation operator to sample this set during the recombination phase in order to create models that reuse valuable building blocks. In this work, a preprocessing of model set by means of clustering is considered.

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DO - 10.1088/1757-899X/734/1/012108

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AN - SCOPUS:85079643568

SN - 1757-8981

VL - 734

JO - IOP Conference Series: Materials Science and Engineering

JF - IOP Conference Series: Materials Science and Engineering

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M1 - 012108

T2 - 2nd International Scientific Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering, MIST: Aerospace 2019

Y2 - 18 November 2019 through 21 November 2019

ER -

Models set pre-processing for genetic programming based evolvement of models of models

Abstract

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