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Proceedings ArticleDOI

Multiobjective intelligence optimal operation of PET polymerization

TLDR
The simulation result indicates that the hybrid network model and model-based multiobjective optimal algorithm are effective in polymerizing of PET with maximum yield and the best quality.
Abstract
A multiobjective intelligence optimal approach in polymerizing of PET with maximum yield and the best quality is proposed. The hybrid neural network based on B-spline and diagonal recursive neural network is used to model the PET process qualities, i.e. the Intrinsic Viscosity and Molecular Weight distribution. Then a hybrid NSGAII-PSO optimal algorithm with penalty functions is applied to solve the multiobjective optimal problem in order to get the best operation conditions. The simulation result indicates that the hybrid network model and model-based multiobjective optimal algorithm are effective.

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Citations
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Proceedings Article

The multi-objective optimization of esterification process based on improved NSGA-III algorithm

TL;DR: Experimental results indicate that PNSGA- III outperforms NSGA-III in terms of IGD metric and HV metric, and reaches a better diversity in the esterification problem.
Journal ArticleDOI

Aplicação de redes Neuro Fuzzy ao processamento de peças automotivas por meio de injeção de polímeros

TL;DR: The purpose of this paper was to use a multilayer perceptron artificial neural network and a radial basis function artificial Neural Network combined with fuzzy sets to produce an inference mechanism that could predict injection mold cycle times and confirmed neurofuzzy networks as an effective alternative to solving such problems.
References
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Journal ArticleDOI

A fast and elitist multiobjective genetic algorithm: NSGA-II

TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI

Particle swarm optimization

TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Journal ArticleDOI

On the Mathematical Modeling of Polymerization Reactors

TL;DR: The mathematical model, which can represent the detailed behavior of a polymer reactor, is an invaluable tool for developing the optimal design and optimal control system for these reactors.
Proceedings ArticleDOI

Viscosity Prediction for PET Process Based on Hybrid Neural Networks

TL;DR: The results indicated that both parallel and serial hybrid neural networks can model for complicated systems well and transfer the solution of nonlinear control strategy into solving for linear systems based on the decomposed models.
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