Authors:
Silvia Curteanu
1
;
Elena-Niculina Dragoi
1
;
Florin Leon
2
and
Cristina Butnariu
1
Affiliations:
1
“Gheorghe Asachi” Technical University of Iasi, Romania
;
2
Faculty of Automatic Control and Computer Engineering, Romania
Keyword(s):
Neural Networks, Support Vector Machines, Differential Evolution, Clonal Selection, Polymerization.
Related
Ontology
Subjects/Areas/Topics:
Application Domains
;
Case Studies
;
Chemical and Petroleum Engineering
;
Health Engineering and Technology Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Simulation and Modeling
;
Simulation Tools and Platforms
Abstract:
A series of modelling methodologies based on artificial intelligence tools are applied to solve a complex real-world problem. Neural networks and support vector machines are used as models and differential evolution and clonal selection algorithms as optimizers for structural and parametric optimization of the models. The goal is to make a comparative analysis of these methods for the case study of the free radical polymerization of styrene, a complex, difficult to model process, where the monomer conversion and molecular masses are predicted as a function of reaction conditions, i.e. temperature, amount of initiator and time. Four modelling methodologies are developed and evaluated in terms of accuracy.