Research Output
The Effect of a Dynamical Layer in Neural Network Prediction of Biomass in a Fermentation Process
  In this paper, computational intelligence has been considered as a tool (software sensor) for state-estimation and prediction of biomass concentration in a simulated fermentation process. Two different paradigms of an artificial neural networks have been introduced as possible computational engines. Inclusion of process dynamics is inherent within the second paradigm, as a pre-processing layer. The constructed computational engines ‘infer’ the production of biomass from easily measured on-line variables. First and second-order non-linear optimisation methods are used to train the neural networks. It is shown that the use of the pre-processing layer which contains dynamical elements, produces better results and shows significant improvement in the convergence rate of the neural networks.

  • Date:

    01 June 1998

  • Publication Status:

    Published

  • Library of Congress:

    QA Mathematics

  • Dewey Decimal Classification:

    519 Probabilities & applied mathematics

  • Funders:

    New Funder

Citation

Soufian, M., Soufian, M. & Dempsey, M. (1998). The Effect of a Dynamical Layer in Neural Network Prediction of Biomass in a Fermentation Process. In Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systemsISBN 3-540-64582-9

Authors

Keywords

Biomass, fermentation, software sensor, neural networks,

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