Application of knowledge information engineering for sake mashing process

Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi

研究成果: Contribution to journalArticle査読

1 被引用数 (Scopus)

抄録

Simulation and control using a mathematical model are often difficult in the sake mashing process, because this process is a complicated process which involves many microorganisms and enzymes. Recently, knowledge information processings, such as fuzzy logic, artificial neural network (ANN), and genetic algorithm (GA), have been developed. These information processings have been applied to control sake mashing process. The fuzzy logic and fuzzy neural network with the extraction of toji's knowledge and experience about the temperature control of the sake mashing process were applied to the temperature control of experimental mashing. Time course data were similar to those from a conventional control based on the decision of the toji. ANN was applied to estimate enzyme activities in koji from the temperature and humidity orbits of koji making process. The suitable courses of temperature and humidity for koji production with the desired values of enzyme activities were determined by applying these models and GA.

本文言語英語
ページ(範囲)167-168
ページ数2
ジャーナルkagaku kogaku ronbunshu
25
2
DOI
出版ステータス出版済み - 3 1999
外部発表はい

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)

フィンガープリント 「Application of knowledge information engineering for sake mashing process」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル