Polymer Gels pp 379-405 | Cite as

Neuro-Evolutive Techniques Applied for Modeling Processes Involving Polymer Gels

  • Silvia CurteanuEmail author
  • Elena-Niculina Dragoi
Part of the Gels Horizons: From Science to Smart Materials book series (GHFSSM)


This chapter presents some applications of artificial neural networks for modeling the polymer gels. A series of general aspects for this topic (neural networks) is first shortly reviewed, emphasizing the main elements of the modeling methodology. Also, general considerations related to the neuro-evolution are discussed, as an appropriate method for obtaining neural networks in an optimal form. The difficulties related to the modeling of polymerization processes are enumerated as motivation for recommending the empirical techniques. The most important part is represented by a series of examples of applications of the neuro-evolutive techniques for modeling the polyacrylamide-based hydrogels. Some examples have been published, but the last three represent new approaches. They refer, mainly, to polyacrylamide-based hydrogels modeled with neural networks of different types, used individually or aggregated in stacks, or with neural networks developed with an evolutionary algorithm (differential evolution algorithm). An inverse neural network modeling was also performed as a particular optimization. Neuro-evolution, based on neural networks and differential evolution algorithm, was also applied for modeling the release of micromolecular compounds from hydrogels.


Polymer gel Neural networks Neuro-evolutive techniques Differential evolution Polyacrylamide-based hydrogels 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Chemical Engineering, Faculty of Chemical Engineering and Environmental Protection“Gheorghe Asachi” Technical UniversityIasiRomania

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