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

Research output: Contribution to journal › Conference article › peer-review

1 Citation (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.

Original language	English
Article number	012108
Journal	IOP Conference Series: Materials Science and Engineering
Volume	734
Issue number	1
DOIs	https://doi.org/10.1088/1757-899X/734/1/012108
Publication status	Published - 29 Jan 2020
Event	2nd International Scientific Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering, MIST: Aerospace 2019 - Krasnoyarsk, Russian Federation Duration: 18 Nov 2019 → 21 Nov 2019

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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.",

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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.

UR - https://www.scopus.com/pages/publications/85079643568

U2 - 10.1088/1757-899X/734/1/012108

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

M3 - Conference article

AN - SCOPUS:85079643568

SN - 1757-8981

VL - 734

JO - IOP Conference Series: Materials Science and Engineering

JF - IOP Conference Series: Materials Science and Engineering

IS - 1

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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

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