A virtual instrument, based on neural networks, for the estimation of octane number in the gasoline produced by refineries is introduced. The stacking approach is proposed to improve the estimation performance of the instrument. The validity of the proposed approach has been verified by comparison with the performance of traditional modeling techniques. The proposed virtual instrument can be used during the maintenance phases of hardware devoted to the measurement of the octane number
Virtual Instruments Based on Stacked Neural Networks to Improve Product Quality Monitoring in a Refinery
FORTUNA, Luigi;GRAZIANI, Salvatore;
2005-01-01
Abstract
A virtual instrument, based on neural networks, for the estimation of octane number in the gasoline produced by refineries is introduced. The stacking approach is proposed to improve the estimation performance of the instrument. The validity of the proposed approach has been verified by comparison with the performance of traditional modeling techniques. The proposed virtual instrument can be used during the maintenance phases of hardware devoted to the measurement of the octane numberFile in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
