In the last few years, problems concerning with both air pollution and quality of products have gained a particular attention in industrial companies. A great interest in new technologies for the process of manufacturing optimization and quality control has raised. Mathematical models for quality control are highly nonlinear and need very expensive and sophisticated instruments. Soft-Computing, an innovative approach for constructing computationally intelligent systems, has just come into the limelight. The quintessence of designing intelligent systems of this kind is Neuro-Fuzzy computing. In this paper a Neuro-Fuzzy prediction model for the quality control of benzene is proposed.
Neuro-Fuzzy Modelling in Petrochemical Industry
BUCOLO, MAIDE ANGELA RITA;GRAZIANI, Salvatore;
1999-01-01
Abstract
In the last few years, problems concerning with both air pollution and quality of products have gained a particular attention in industrial companies. A great interest in new technologies for the process of manufacturing optimization and quality control has raised. Mathematical models for quality control are highly nonlinear and need very expensive and sophisticated instruments. Soft-Computing, an innovative approach for constructing computationally intelligent systems, has just come into the limelight. The quintessence of designing intelligent systems of this kind is Neuro-Fuzzy computing. In this paper a Neuro-Fuzzy prediction model for the quality control of benzene is proposed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
