Prediction of hydrogen concentration in nuclear power plant containment under severe accidents using cascaded fuzzy neural networks-Reference-Cited by-同舟云学术

Prediction of hydrogen concentration in nuclear power plant containment under severe accidents using cascaded fuzzy neural networks

Published:2016-04 Issue: Volume:300 Page:393-402
ISSN:0029-5493
Container-title:Nuclear Engineering and Design
language:en
Short-container-title:Nuclear Engineering and Design

Author:

Choi Geon Pil,Kim Dong Yeong,Yoo Kwae Hwan,Na Man Gyun

Funder

National Research Foundation

Publisher

Elsevier BV

Subject

Mechanical Engineering,Waste Management and Disposal,Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Reference23 articles.

1. Mitigation of hydrogen hazards in severe accidents in nuclear power plants;Abou-Rjeily,2011

2. Nuclear power plant transient diagnostics using artificial neural networks that allow don’t-know classifications;Bartal;Nucl. Technol.,1995

3. Nuclear power plant diagnostics using an artificial neural network;Bartlett;Nucl. Technol.,1992

4. Application of neural networks to a connectionist expert system for transient identification in nuclear power plants;Cheon;Nucl. Technol.,1993

5. Cascaded fuzzy neural network model based on syllogistic fuzzy reasoning;Duan;IEEE Trans. Fuzzy Syst.,2001

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