Predicting effluent suspended solids from a dynamic enhanced biological phosphorus removal system using a neurogenetic model

W. C. Chang*, C. F. Ouyang, J. S. Chen

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

2 Scopus citations

Abstract

This study applies the neurogenetic model, i.e. a hybrid intelligent system combining genetic algorithm (GA) with artificial neural networks (ANN), to accurately predict effluent suspended solids concentrations from an enhanced biological phosphorus removal (EBPR) system under typical diurnal variation of municipal wastewater. Continuous-flow pilot plant experiments with automatic monitoring and control facilities were performed to assess the model's applicability. The effluent suspended solids concentrations from the experiments closely corresponded to those predicted by the neurogenetic model developed herein.

Original languageEnglish
Pages (from-to)1185-1203
Number of pages19
JournalJournal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering
Volume33
Issue number6
DOIs
StatePublished - 1998

Keywords

  • Artificial neural network (ANN)
  • Dynamic
  • Enhanced biological phosphorus removal (EBPR) process
  • Genetic algorithm (GA)

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