Construction of COD simulation model for activated sludge process by fuzzy neural network

Shuta Tomida, Taizo Hanai, Naoyasu Ueda, Hiroyuki Honda, Takeshi Kobayashi

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Fuzzy neural network (FNN) was applied to construct a simulation model for estimating the effluent chemical oxygen demand (COD) value of an activated sludge process in a 'U' plant, in which most of process variables were measured once an hour. The constructed FNN model could simulate periodic changes in COD with high accuracy. Comparing the simulation result obtained using the FNN model with that obtained using the multiple regression analysis (MRA) model, it was found that the FNN model had 3.7 times higher accuracy than the MRA model. The FNN models corresponding to each of the four seasons were also constructed. Analyzing the fuzzy rules acquired from the FNN models after learning, the operational characteristic of this plant could be elucidated. Construction of the simulation model for another plant 'A', in which process variables were measured once a day, was also carried out. This FNN model also had a relatively high accuracy.

Original languageEnglish
Pages (from-to)215-220
Number of pages6
JournalJournal of Bioscience and Bioengineering
Issue number2
Publication statusPublished - 1999
Externally publishedYes


  • Activated sludge process
  • Chemical oxygen demand
  • Fuzzy neural network
  • Simulation

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology


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