Thermal power prediction of nuclear power plant using neural network and parity space model
- 1 April 1991
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Nuclear Science
- Vol. 38 (2), 866-872
- https://doi.org/10.1109/23.289402
Abstract
A power prediction system was developed using an artificial neural network paradigm that was combined with a parity space signal validation technique. The parity space signal validation algorithm for input preprocessing and a backpropagation network algorithm for network learning are used for the power prediction system. Case studies were performed with emphasis on the applicability of the network in a steady-state high-power level. The studies reveal that these algorithms can precisely predict the thermal power in a nuclear power plant. They also show that the error signals resulting from instrumentation problems can be properly treated even when the signals comprising various patterns are noisy or incompleteKeywords
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