Published 2002 | Version v1
Miscellaneous Open

A comparison between genetic algorithms and neural networks for optimizing fuel recharges in BWR

Creators

  • 1. Instituto Nacional de Investigaciones Nucleares, Depto. Sistemas Nucleares, A.P. 18-1027, 11801 Mexico D.F. (Mexico)
  • 2. Universidad de Granada (Spain)

Description

In this work the results of a genetic algorithm (AG) and a neural recurrent multi state network (RNRME) for optimizing the fuel reload of 5 cycles of the Laguna Verde nuclear power plant (CNLV) are presented. The fuel reload obtained by both methods are compared and it was observed that the RNRME creates better fuel distributions that the AG. Moreover a comparison of the utility for using one or another one techniques is make. (Author)

Availability note (English)

Available from INIS in electronic form

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Additional details

Additional titles

Original title (Spanish)
Una comparacion entre algoritmos geneticos y redes neuronales para optimizar recargas de combustible en BWR's

Publishing Information

Imprint Pagination
4 p.
Report number
INIS-MX--1241

Conference

Title
12. ININ-SUTIN Technical and Scientific Congress
Dates
4-6 Dec 2002
Place
Salazar, Estado de Mexico (Mexico)

INIS

Country of Publication
Mexico
Country of Input or Organization
Mexico
INIS RN
34030734
Subject category
S99: GENERAL AND MISCELLANEOUS;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; ARTIFICIAL INTELLIGENCE; BWR TYPE REACTORS; CROSS SECTIONS; EXPERIMENTAL DATA; FUEL ELEMENTS; NEURAL NETWORKS; NEUTRON DIFFUSION EQUATION; NUCLEAR POWER PLANTS; REACTOR FUELING
Descriptors DEC
DATA; DIFFERENTIAL EQUATIONS; ENRICHED URANIUM REACTORS; EQUATIONS; INFORMATION; MATHEMATICAL LOGIC; NUCLEAR FACILITIES; NUMERICAL DATA; POWER PLANTS; POWER REACTORS; REACTOR COMPONENTS; REACTORS; THERMAL POWER PLANTS; THERMAL REACTORS; WATER COOLED REACTORS; WATER MODERATED REACTORS