Quantification of favorableness to foods by information processing on human sense
Quantification of favorableness to foods by information processing on human sense
批准号:
09838017
负责人:
HONDA Hiroyuki
金额:
$2.05万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
1997
资助国家:
日本
项目状态:
已结题
起止时间:
1997 至 1998
中文摘要
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英文摘要
Quantification of favorableness to foods such as beer, Ginjo sake and coffee, was carried out and the following results were obtained.(1) Quality modeling of coffee was constructed. The analytical data from 67 samples obtained by dripping and those sensory evaluation data were collected. When fuzzy neural network (FNN) was applied to the modeling, the FNN model acquired showed the higher accuracy on estimation of sensory evaluation, compared with the model by the conventional method, multi-regression analysis.(2) FNN and HFNN (hierarchical fuzzy neural network) were applied in order to construct the models estimated from the analysis data for the sensory evaluations of various Ginjo sake samples. Errors estimated by FNN and HFNN models were about 10% and 7%, respectively. Selected input variables using FNN and HFNN were in good agreement with expert's experiences. By the analysis of fuzzy rules, qualitative effects of these input variables were almost the same as expert's experiences.( … More 3) Models for sensory evaluation of beer and beer brewing process were constructed using FNN.A new method for optimal model selection using genetic algorithm and SWEEP operator method was compared with a conventional method using parameter increasing method. As the result, the new method was useful for the optimal model selection by simplifying the model structure, improving the reliability of fuzzy rules and fastening the calculation speed (about 10 times as fast as conventional method) for constructing the model with high accuracy. The important variables were selected as the input variables and the obtained fuzzy rules in modeling coincided well with knowledge data bases acquired by process operators.(4) Fundamental research on tasting sensor was carried out. The gene encoding a gustatory receptor was cloned and the purification method of the receptor protein from recombinant Escherichia coli was established. When the purified protein was dipped on the sensor tip (i.d. 3mm) of surface plasmon resonance analyzer, the change of analyzer output could be detected. Therefore, the tasting sensor associated with a specific sensing molecule, gustatory receptor, is possible to be developed. Less
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Taizo Hanai, Hideki Noguchi, Hiroyuki Honda, Takeshi Furuhashi, Yoshiki Uchikawa, Masahiro Kamiya, Tohoru Ishii and Takeshi Kobayashi: "Quality model of Ginjo sake using hierarchical fuzzy neural network (in Japanese)" Nihon Fuzzy Gakkaishi. 10(2). 299-30
Taizo Hanai、Hideki Noguchi、Hiroyuki Honda、Takeshi Furuhashi、Yoshiki Uchikawa、Masahiro Kamiya、Tohoru Ishii 和 Takeshi Kobayashi:“使用分层模糊神经网络的 Ginjo 清酒质量模型(日语)”Nihon Fuzzy Gakkaishi。
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发表时间:
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影响因子:
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作者:
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通讯作者:
花井泰三: "知識情報処理を用いたコーヒーの品質モデル" 日本食品科学工学会誌. 44(8). 560-568 (1997)
Taizo Hanai:“使用知识信息处理的咖啡质量模型”日本食品科学技术学会杂志 44(8)(1997)。
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Taizo Hanai, Eiji Ohkusu, Hiroyuki Honda, Fumio Ito, Motohiko Sugiura, Ichiro Asano and Takeshi Kobayashi: "Quality modeling for coffee using the knowledge information processing (in Japanese)" Nippon Shokuhin Kagaku Kogaku Kaishi. 44(8). 560-568 (1997)
Taizo Hanai、Eiji Ohkusu、Hiroyuki Honda、Fumio Ito、Motohiko Sugiura、Ichiro Asano 和 Takeshi Kobayashi:“使用知识信息处理的咖啡质量建模(日语)”Nippon Shokuhin Kagaku Kogaku Kaishi。
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Taizo-Hanai, Eiji Ohkusu, Toshihiko Ohki, Hiroyuki Honda, Hisao Tohyama, Takahiro Muramatsu and Takeshi Kobayashi: "Application of an artificial neural network and genetic algorithm for determication of process orbits in the koji making process" Journal o
Taizo-Hanai、Eiji Ohkusu、Toshihiko Ohki、Hiroyuki Honda、Hisao Tohyama、Takahiro Muramatsu 和 Takeshi Kobayashi:“人工神经网络和遗传算法在曲制作过程中确定过程轨道的应用”期刊
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作者:
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通讯作者:
T.Hanai: "Application of an artificial neural network and genetic algorithm for determination of process orbits in the koji making process" J.Biosci.Bioeng.87・4. 320-326 (1999)
T.Hanai:“人工神经网络和遗传算法在曲制作过程中确定过程轨道的应用”J.Biosci.Bioeng.87・4(1999)。
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批准号:--
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