000 01800nmc a2200277 4500
005 20260520005606.0
008 260224s2001 xxu ing
041 _aInglés
245 0 0 _aARTIFICIAL NEURAL NETWORKS APPLIED TO THE OPERATION OF A FLUID CATALYTIC CRACKING (FCC) UNIT
_bSPE 69501
260 _aDallas, Texas
_bSociety of Petroleum Engineers
_c2001
270 _a12/09/06 ; 17/07/01
520 _aA model, based on artificial neural networks (ANN), for a fluid catalytic cracking (FCC) unit is developed. The ANN model of the plant was developed using process and laboratory data directly from a refinery data acquisition system. And it used to predict process variables and estimate several product quality properties. The empirical model was accurate up to 98.0 % when tested on experimental data not used during training, which is an outstanding performance. The present paper shows how a neural network, three-layered perceptron, can be used effectively to simulate the actual behaviour of refining units, specifically a fluid catalytic cracking (FCC) unit.
942 _cCONGTP
100 1 _aPérez, José R.
_96164
100 1 _aLópez, Roberto
_96165
100 1 _aDassori, Carlos G.
_96166
100 1 _aRanson, Aaron
_96167
111 2 _aLatin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina)
_95738
700 1 _aLópez, Roberto
_96165
700 1 _aDassori, Carlos G.
_96166
700 1 _aRanson, Aaron
_96167
711 2 _aLatin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina)
_95738
800 1 _aPérez, José R.
_96164
999 _c131012
_d131012
856 _uhttps://biblioteca.iapg.org.ar/ArchivosAdjuntos/LACPEC2001/Spe69501.pdf