Title :
Application of neural networks and fuzzy systems to power plants
Author :
Uhrig, Robert E. ; Tsoukalas, Lefieri H. ; Ikonomopoulos, Andreas
Author_Institution :
Tennessee Univ., Knoxville, TN, USA
fDate :
27 Jun- 2 Jul 1994
Abstract :
Many of the problems that have occurred in the operation of nuclear power plants have been attributable in some measure to operator error, and therefore could have been prevented or alleviated by automation. Neural networks and fuzzy logic systems offer an interesting, challenging, and productive means of addressing many such problems. Although much of the work described has been to demonstrate feasibility of specific approaches, the results are encouraging and indicate that neural network and fuzzy logic systems techniques have the potential to enhance the performance, operability, and safety of nuclear power plants in a cost effective way
Keywords :
fission reactor operation; fission reactor safety; fuzzy logic; neural nets; nuclear engineering computing; nuclear power stations; automation; fuzzy systems; neural networks; nuclear power plants; operability; performance; safety; Accidents; Artificial intelligence; Fuzzy logic; Fuzzy systems; Laboratories; Monitoring; Neural networks; Pattern recognition; Power generation; Safety;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374800