DocumentCode
2307919
Title
Octane number prediction in a reforming plant
Author
Chibaro, E. ; Fichera, S. ; Muscato, G.
Author_Institution
Ist. di Macchine, Catania Univ., Italy
Volume
4
fYear
2000
fDate
2000
Firstpage
403
Abstract
In this work a neural network for the prediction of the complex and nonlinear behaviour of a catalytic reforming of a refinery has been developed. In a fuel refinery reforming is a conversion process to increase the octane number of the desulphurated heavy naphtha in charge. The neural model has been trained and validated on experimental measurements. The results confirmed the suitability of the proposed approach
Keywords
chemical engineering computing; learning (artificial intelligence); neural nets; oil refining; process control; catalytic reforming; desulphurated heavy naphtha; learning; neural network; nonlinear behaviour prediction; octane number; oil refinery; process control; reforming plant; Chemical processes; Economic forecasting; Electrical equipment industry; Feedforward systems; Fuel processing industries; Industrial control; Neural networks; Process control; Production; Refining;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.860805
Filename
860805
Link To Document