ARTIFICIAL NEURAL NETWORKS APPLIED TO THE OPERATION OF A FLUID CATALYTIC CRACKING (FCC) UNIT SPE 69501
Language: Inglés Series: Pérez, José R ; Publication details: Dallas, Texas Society of Petroleum Engineers 2001Online resources: Summary: 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.| Current library | Status | Barcode | |
|---|---|---|---|
| Biblioteca virtual | Not for loan | 200003067 |
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.
