BECAS
MAFFI Juan MartÍn
congresos y reuniones científicas
Título:
Neural Network Models for the Optimization of Polymer Plants: The Case of the Industrial Processes of Styrenic Polymers.
Autor/es:
MAFFI, J. M.; ESTENOZ, D.
Lugar:
Buenos Aires
Reunión:
Congreso; 11th World Congress of Chemical Engineering; 2023
Resumen:
The goal of this work is to develop mathematical models based on supervised learning algorithms (a type of artificial intelligence models) in order to predict, analyze and optimize the industrial production plants of styrenic products such as General Purpose Polystyrene (GPPS) and High Impact Polystyrene (HIPS). A benchmark polymerization model is used to compare the performance of the proposed models.Materials
