Adaptive Vector Quantization Optimized by Genetic Algorithm for Real-Time Diagnosis Through Fuzzy Sets-Reference-Cited by-同舟云学术

Adaptive Vector Quantization Optimized by Genetic Algorithm for Real-Time Diagnosis Through Fuzzy Sets

Published:1997-12 Issue:3 Volume:120 Page:188-197
ISSN:0029-5450
Container-title:Nuclear Technology
language:en
Short-container-title:Nuclear Technology

Author:

Alvarenga Marco Antonio Bayout¹,Martinez Aquilino Senra²,Schirru Roberto²

Affiliation:

1. Comissão Nacional de Energia Nuclear, Rua General Severiano 90 sala 412 22294-900, Rio de Janeiro, Brazil

2. Coordenação dos Programas de Pōs-Graduação de Engenharia da Universidade Federal do Rio de Janeiro, Caixa Postal 68509, 21945-970, Rio de Janeiro, Brazil

Publisher

Informa UK Limited

Subject

Condensed Matter Physics,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

https://www.tandfonline.com/doi/pdf/10.13182/NT97-A35410

Reference7 articles.

1. Nuclear Power Plant Transient Diagnostics Using Artificial Neural Networks That Allow “Don’t-Know” Classifications

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1. A NEURO-FUZZY SYSTEM TO SUPPORT THE ATTENTION DIRECTION OF NUCLEAR POWER PLANT OPERATORS;Brazilian Journal of Operations & Production Management;2015-06-30

2. Nuclear In-core Fuel Reload Design: The Trajectory of a Sequence of Projects;Lecture Notes in Computer Science;2014

3. An efficient Neuro-Fuzzy approach to nuclear power plant transient identification;Annals of Nuclear Energy;2011-06

4. A model for preventive maintenance planning by genetic algorithms based in cost and reliability;Reliability Engineering & System Safety;2006-02

5. Recurrent neuro-fuzzy system for fault detection and isolation in nuclear reactors;Advanced Engineering Informatics;2005-01