ARTIFICIAL NEURAL NETWORKS APPLIED TO THE OPERATION OF A FLUID CATALYTIC CRACKING (FCC) UNIT SPE 69501
Pérez, José R. López, Roberto Dassori, Carlos G. Ranson, Aaron
ARTIFICIAL NEURAL NETWORKS APPLIED TO THE OPERATION OF A FLUID CATALYTIC CRACKING (FCC) UNIT SPE 69501 - Dallas, Texas Society of Petroleum Engineers 2001 - Pérez, José R. .
A 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.
ARTIFICIAL NEURAL NETWORKS APPLIED TO THE OPERATION OF A FLUID CATALYTIC CRACKING (FCC) UNIT SPE 69501 - Dallas, Texas Society of Petroleum Engineers 2001 - Pérez, José R. .
A 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.
