PEANO and on-line monitoring techniques for calibration reduction of process instrumentation in power plants

被引：0
作者：
Fantoni, PF [1 ]
机构：
[1] OECD, Inst Energiteknikk, Halden Reactor Project, N-1751 Halden, Norway
来源：
POWER PLANT SURVEILLANCE AND DIAGNOSTICS: APPLIED RESEARCH WITH ARTIFICIAL INTELLIGENCE | 2002年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
引用
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页码：355 / 376
页数：22
相关论文
共 15 条
[1]  
[Anonymous], Pattern Recognition With Fuzzy Objective Function Algorithms
[2]  
BARTAL Y, 1995, NUCL TECHNOLOGY, V110
[3]  
*EPRI, 2000, TR104965R1 NRC SER
[4]  
FANTONI P, 1996, SYMBOLIC COMPUTATION, pCH17
[5]  
FANTONI P, 1995, P SMORN 7 AV FRANC
[6]  
FANTONI P, 1994, P IAEA SPEC M ADV IN
[7]  
FANTONI P, 1996, P NPIC HMIT 96 PENNS
[8]   Multiple-failure signal validation in nuclear power plants using artificial neural networks [J].
Fantoni, PF ;
Mazzola, A .
NUCLEAR TECHNOLOGY, 1996, 113 (03) :368-374
[9]   A neuro-fuzzy model applied to full range signal validation of PWR nuclear power plant data [J].
Fantoni, PF .
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2000, 29 (02) :305-320
[10]   A Pattern Recognition Artificial Neural Networks based model for Signal Validation in nuclear power plants [J].
Fantoni, PF ;
Mazzola, A .
ANNALS OF NUCLEAR ENERGY, 1996, 23 (13) :1069-1076
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