DOI: 10.1615/ICHMT.1992.IntForumExpSysCompSimEE
ISBN Print: 978-1-56700-486-1
APPLICATION OF NEURAL NETWORKS TO CONNECTIONIST EXPERT SYSTEM FOR IDENTIFICATION OF TRANSIENTS IN NUCLEAR POWER PLANTS
ABSTRACT
The expert systems that have neural networks for their knowledge bases are called connectionist expert systems. The back-propagation neural network model is applied to the connectionist expert system for the identification of transients in nuclear power plants. Several powerful features of neural network-based expert systems over traditional rule-based expert systems are discussed. The general mapping capability of the neural networks enables to identify a transient easily. The case studies are performed with emphasis on the applicability of the neural networks to the classification problems. It is revealed that the neural network model can identify the transient properly, even when incomplete, untrained, or sensor-failed symptoms are given. It is also shown that multiple transients are easily identified.