A neural-network controlled dynamic evolutionary scheme for global molecular geometry optimization

• Autorzy: Anna Styrcz , Janusz Mrozek , Grzegorz Mazur
• Języki publikacji: EN

Abstrakty

EN

A novel, neural network controlled, dynamic evolutionary algorithm is proposed for the purposes of molecular geometry optimization. The approach is tested for selected model molecules and some molecular systems of importance in biochemistry. The new algorithm is shown to compare favorably with the standard, statically parametrized memetic algorithm.

Słowa kluczowe

EN

global optimization; memetic algorithm; molecular geometry

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2011
• Tom: 21
• Numer: 3
• Strony: 559-566

Daty

wydano

2011

otrzymano

2010-08-14

poprawiono

2011-01-31

Twórcy

autor

Anna Styrcz

• Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland

autor

Janusz Mrozek

• Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland

autor

Grzegorz Mazur

• Department of Computational Methods in Chemistry, Jagiellonian University, ul. R. Ingardena 3, 30-060 Cracow, Poland

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Identyfikatory

DOI

10.2478/v10006-011-0044-8