1 |
C. Allison, Comparison between MAAP, MELCOR, and SCDAP/RELAP5, Proceedings of the Workshop on Severe Accident Research in Japan (SARJ-97), JAERI (Japan atomic energy research institute), Yokohama, Japan, 1998 Oct 6e8, pp. 396-401.
|
2 |
K. Chen, C. Wang, Support vector regression with genetic algorithms in forecasting tourism demand, Tourism Manage. 28 (2007) 215-226.
DOI
|
3 |
Z. Yangping, Z. Bingquan, W. Dongxin, Application of genetic algorithms to fault diagnosis in nuclear power plants, Reliab. Eng.Syst. Safe. 67 (2000) 153-160.
DOI
|
4 |
J.W. Hines, D.J. Wrest, R.E. Uhrig, Signal validation using an adaptive neural fuzzy inference system, Nucl. Technol. 199 (1997) 181-193.
|
5 |
Y.G. No, J.H. Kim, M.G. Na, D.H. Lim, K.I. Ahn, Monitoring severe accidents using AI techniques, Nucl. Eng. Technol. 44 (2012) 393-404.
DOI
|
6 |
M.G. Na, A neuro-fuzzy inference system for sensor failure detection using wavelet denoising, PCA and SPRT, J. Korean Nucl. Soc. 33 (2001) 483-497.
|
7 |
J. Garvey, D. Garvey, R. Seibert, J.W. Hines, Validation of online monitoring techniques to nuclear plant data, Nucl. Eng. Technol. 39 (2007) 149-158.
DOI
|
8 |
M. Marseguerra, E. Zio, Fault diagnosis via neural networks: the Boltzmann machine, Nucl. Sci. Eng. 117 (1994) 194e200.
DOI
|
9 |
M.G. Na, W.S. Park, D.H. Lim, Detection and diagnostics of loss of coolant accident using support vector machines, IEEE Trans. Nucl. Sci. 55 (2008) 628-636.
DOI
|
10 |
M Claudia, S. Rocco, E. Zio, A support vector machine integrated system for the classification of operation anomalies in nuclear components and systems, Reliab. Eng. Sys. Safe. 92 (2007) 593-600.
DOI
|
11 |
I. Lindholm, E. Pekkarinen, H. Sjovall, Evaluation of reflooding effects on an overheated boiling water reactor core in a small steam-line break accident using MAAP, MELCOR, and SCDAP/RELAP5 computer codes, Nucl. Technol. 112 (1995) 42-57.
DOI
|
12 |
R. Gutierrez-Osuna, CSCE666: Pattern Analysis, Radial basis functions lecture notes [PowerPoint slides], Dept. of Computer Science & Engineering, Texas A&M University, Texas, U.S., 2011. Retrieved from http://research.cs.tamu.edu/prism/lectures/pr/pr_l19.pdf.
|
13 |
N. Xin, X. Gu, H. Wu, Y. Hu, Z. Yang, Application of genetic algorithm-support vector regression (GA-SVR) for quantitative analysis of herbal medicines, J.Chemometr. 26 (2012) 353-360.
DOI
|
14 |
E.B. Bartlett, R.E. Uhrig, Nuclear power plant diagnostics using an artificial neural network, Nucl. Technol. 97 (1992) 272-281.
DOI
|