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Neuroevolutive Algorithms Applied for Modeling Some Biochemical Separation Processes

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Artificial Neural Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2190))

Abstract

Combining artificial neural networks with evolutive/bioinspired approaches is a technique that can solve a variety of issues regarding the topology determination and training for neural networks or for process optimization. In this chapter, the main mechanisms used in neuroevolution are discussed and some biochemical separation examples are given to underline the efficiency of these tools. For the current case studies (reactive extraction of folic acid and pertraction of vitamin C), the bioinspired metaheuristic included in the neuroevolutive procedures is represented by Differential Evolution, an algorithm that has shown a great potential to solve a variety of problems from multiple domains.

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Author information

Authors and Affiliations

  1. Faculty of Chemical Engineering and Environmental Protection “Cristofor Simionescu”, “Gheorghe Asachi” Technical University of Iasi, Iasi, Romania

    Silvia Curteanu, Elena-Niculina Dragoi, Alexandra Cristina Blaga & Dan Cascaval

  2. Faculty of Medical Bioengineering, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania

    Anca Irina Galaction

Authors
  1. Silvia Curteanu
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  2. Elena-Niculina Dragoi
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  3. Alexandra Cristina Blaga
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  4. Anca Irina Galaction
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  5. Dan Cascaval
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Editor information

Editors and Affiliations

  1. Chemistry, Oxford University, Oxford, UK

    Hugh Cartwright

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Curteanu, S., Dragoi, EN., Blaga, A.C., Galaction, A.I., Cascaval, D. (2021). Neuroevolutive Algorithms Applied for Modeling Some Biochemical Separation Processes. In: Cartwright, H. (eds) Artificial Neural Networks. Methods in Molecular Biology, vol 2190. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0826-5_5

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  • DOI: https://doi.org/10.1007/978-1-0716-0826-5_5

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0825-8

  • Online ISBN: 978-1-0716-0826-5

  • eBook Packages: Springer Protocols

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