Automatic fuzzy modeling for Ginijo sake brewing process using fuzzy neural networks

Taizo Hanai, Akemi Katayama, Hiroyuki Honda, Takeshi Kobayashi

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Automatic fuzzy modeling was studied for Ginjo sake brewing process using a fuzzy neural network (FNN). From the analysis of data for 25 Ginjo sake brewings, the control period was separated into 4 regions. We constructed 4 FNN models for fuzzy control in each control region. Acquired models could estimate the set temperature precisely, and acquired rules coincided well with the experience of Toji. The suitability of acquired models was confirmed by the simulation proposed by us.

Original languageEnglish
Pages (from-to)94-100
Number of pages7
JournalJOURNAL OF CHEMICAL ENGINEERING OF JAPAN
Volume30
Issue number1
DOIs
Publication statusPublished - Jan 1 1997
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)

Fingerprint Dive into the research topics of 'Automatic fuzzy modeling for Ginijo sake brewing process using fuzzy neural networks'. Together they form a unique fingerprint.

  • Cite this