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International Work-Conference on Artificial Neural Networks

IWANN 2015: Advances in Computational Intelligence pp 237–249Cite as

Evolutionary Hybrid Configuration Applied to a Polymerization Process Modelling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9095))

Abstract

A modelling procedure based on hybrid configuration composed of artificial neural networks, differential evolution and clonal selection algorithms is developed and applied in this work. The neural network represents the model of the system, while the differential evolution and clonal selection algorithms perform a simultaneous topological and parametric optimization of the model. The results indicated that the combination of the two optimizers produces better results compared with each of them working separately. As case study, styrene polymerization, a complex process which is difficult to model when taking into consideration all the internal interactions, was chosen. Neural networks, designed in an optimal form, proved to be adequate tools for modelling this system.

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Author information

Authors and Affiliations

  1. Faculty of Chemical Engineering and Environmental Protection, “Gheorghe Asachi” Technical University of Iasi, 73, Prof. Dr. Doc. D. Mangeron Blvd., 700050, Iasi, Romania

    Silvia Curteanu & Elena-Niculina Dragoi

  2. Clinical Emergency Hospital “Prof. Dr. N. Oblu”, Str. Ateneului, 700309, Iasi, Romania

    Vlad Dafinescu

Authors
  1. Silvia Curteanu
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  2. Elena-Niculina Dragoi
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  3. Vlad Dafinescu
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Corresponding author

Correspondence to Elena-Niculina Dragoi .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. Department of Electronics Technology, University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Spain

    Andreu Catala

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© 2015 Springer International Publishing Switzerland

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Curteanu, S., Dragoi, EN., Dafinescu, V. (2015). Evolutionary Hybrid Configuration Applied to a Polymerization Process Modelling. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2015. Lecture Notes in Computer Science(), vol 9095. Springer, Cham. https://doi.org/10.1007/978-3-319-19222-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-19222-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19221-5

  • Online ISBN: 978-3-319-19222-2

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