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The Application of Neural Networks for Fault Diagnosis in Nuclear Reactors

N.A. Jalel,Helen Nicholson-1990-11-01-White Rose Research Online (University of Leeds, The University of Sheffield, University of York)

TL;DRAbstract

In recent years considerable work has been done in the field of neural networks due to the recent development of effective learning algorithms and the results of thier applications have suggested that they can provide useful tools for solving practical problems. Artificial neural networks are mathematical models of theorized mind and brain activity. They are aimed to explore and reproduce human information processing tasks such as speech, vision, knowledge processing and control. The possibility of using neural networks for fault and accident diagnosis in the Loss of Fluid Test (LOFT( reactor, a small scale pressurised water reactor, is examined and explained in this paper.

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In recent years considerable work has been done in the field of neural networks due to the recent development of effective learning algorithms and the results of thier applications have suggested that they can provide useful tools for solving practical problems. Artificial neural networks are mathematical models of theorized mind and brain activity. They are aimed to explore and reproduce human information processing tasks such as speech, vision, knowledge processing and control. The possibility of using neural networks for fault and accident diagnosis in the Loss of Fluid Test (LOFT( reactor, a small scale pressurised water reactor, is examined and explained in this paper.

Keywords

Artificial neural networkComputer scienceField (mathematics)Artificial intelligenceFault (geology)Machine learningControl engineeringEngineering

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