Artificial neural network model with a culture database for prediction of acidification step in cheese production

被引:15
|
作者
Horiuchi, J
Shimada, T
Funahashi, H
Tada, K
Kobayashi, M
Kanno, T
机构
[1] Kitami Inst Technol, Dept Chem Syst Engn, Hokkaido 0908507, Japan
[2] Kitami Inst Technol, Int Students Ctr, Kitami, Hokkaido 0908507, Japan
[3] Snowbrand Co Ltd, Sapporo Res Ctr, Higashi Ku, Sapporo, Hokkaido 0650043, Japan
关键词
neural network; euclid distance; lactic acid fermentation; cheese; acidification; modeling;
D O I
10.1016/j.jfoodeng.2003.09.005
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
An artificial neural network with a culture database was developed to predict process behavior in cheese production. Based on the experimental investigations, it was found that the determination of the final process time of the acidification step, followed by rennet addition, is the key to successful operation of cheese processing. In order to determine the optimal timing for the rennet addition, it is practically useful to develop a model which can predict the final process time in the acidification process for successful cheese production. Therefore, an artificial neural network system with a culture database containing various operating data, in which the learning data for back propagation were selected from a culture database based on the Euclid distance, was examined. The system enabled successful prediction the final process time in the acidification process based on several operating data and the culture database. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:459 / 465
页数:7
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