Application of Artificial Neural Networks, Fuzzy Neural Networks, and Genetic Algorithms to Biochemical Engineering View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

Taizo Hanai , Hiroyuki Honda , Takeshi Kobayashi

ABSTRACT

In bioengineering processes, many complex and nonlinear biochemical reactions occur simultaneously, since a variety of microorganisms and enzymes are present in the system. Thus, it may be difficult to describe the process with conventional mathematical models and use such models for process control. Recently soft computing methods such as artificial neural networks, fuzzy reasoning, fuzzy neural networks, and the genetic algorithm, have been applied to the modeling and control of bioengineering processes. In this chapter, three applications to the Japanese sake making process are reviewed, and the manner in which soft computing methods can help in the interpretation and control of this process are discussed. Knowledge extraction from a sake brewing expert, called TOJI, was carried out with the aim of optimizing the temperature control of the mashing process using fuzzy reasoning and fuzzy neural networks. We also discuss the determination of optimum process temperature and humidity using artificial neural networks and genetic algorithms. More... »

PAGES

135-159

References to SciGraph publications

Book

TITLE

Soft Computing Approaches in Chemistry

ISBN

978-3-642-53507-9
978-3-540-36213-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-36213-5_6

DOI

http://dx.doi.org/10.1007/978-3-540-36213-5_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023162317


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