QUALITY MODELING OF GINJO SAKE USING A NEURAL-NETWORK AND GENETIC ALGORITHM

被引：0

作者：

KAKAMU, A ^{[1
]}

HANAI, T ^{[1
]}

HONDA, H ^{[1
]}

KOBAYASHI, T ^{[1
]}

机构：

[1] NAGOYA UNIV,FAC ENGN,DEPT BIOTECHNOL,CHIKUSA KU,NAGOYA,AICHI 46401,JAPAN

来源：

SEIBUTSU-KOGAKU KAISHI-JOURNAL OF THE SOCIETY FOR FERMENTATION AND BIOENGINEERING | 1995年 / 73卷 / 05期

关键词：

NEURAL NETWORK; SENSORY EVALUATION; GENETIC ALGORITHM; QUALITY MODELING; GINJO SAKE;

D O I：

暂无

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

This paper deals with the quality modeling of Ginjo sake using a neural network (NN) and genetic algorithm (GA). A NN model was constructed to estimate 7 sensory evaluations concerning the quality of Ginjo sake from 18 chemical component analytical values. The performance index, J, of the NN model was significantly small compared with that obtained using multiple regression analysis (MRA). Using the model, analytical data on the chemical components was estimated from the 7 given sensory evaluation values by means of a genetic algorithm, which was employed as an optimizing method. It was found that almost all the estimated values coincided with the actual values within an error range of less than 0.3.

引用

页码：387 / 395

页数：9