Using Hopfield neural network to optimize fuel rod loading patterns in VVER/1000 reactor by applying axial variation of enrichment distribution-Reference-Cited by-同舟云学术

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Using Hopfield neural network to optimize fuel rod loading patterns in VVER/1000 reactor by applying axial variation of enrichment distribution

Published:2014-08 Issue: Volume:21 Page:501-508
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Tayefi Shima,Pazirandeh Ali

Publisher

Elsevier BV

Subject

Software

Reference27 articles.

1. A theoretical investigation into the performance of the Hopfield model;Aiyer;IEEE Trans. Neural Netw.,1990

2. Parameterless evolutionary algorithm applied to the nuclear reload problem;Caldas;Ann. Nucl. Energy,2008

3. Fortran 90/95 for Scientists and Engineers;Chapman Stephan,1988

4. Fortran 95;Counihan,1996

5. Recarga de Reatores Nucleares Utilizando Redes Conectivas de Colônias Artificiais;De Lima,2005

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