BioTOOL—a Readily and Flexible Biogas Rate Prediction Tool for End-users

Sebastian Hien, Joachim Hansen, Jörg E. Drewes, Konrad Koch

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This study illustrates an approach to provide an easily manageable tool for end-users to predict the biogas production rate to ease the transition to a flexible and proactive operation of digesters at both biogas plants as well as at wastewater treatment plants. To provide a high flexibility to end-users but keep BioTOOL easily manageable, the approach uses a pre-trained artificial neural networks library consisting of different variable combinations. In BioTOOL’s workflow, end-user will be asked for current measurements disregarding the combination of those. BioTOOL uses a seek-and-implement method to find the correct stored network for the entered input. This approach results in predictions similar to the optimized pre-trained network. It has been demonstrated that the idea of a flexible prediction tool could be fully realized.

Original languageEnglish
Pages (from-to)87-94
Number of pages8
JournalEnvironmental Modeling and Assessment
Volume24
Issue number1
DOIs
StatePublished - 1 Feb 2019

Keywords

  • Artificial neural network
  • Biogas prediction tool
  • Power generation prediction
  • Wastewater treatment

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