Determination of the blending ratio of regular coffee samples by information technology

Osamu Tominaga; Fumio Ito; Taizo Hanai; Hiroyuki Honda; Takeshi Kobayashi

doi:10.1252/jcej.35.137

Determination of the blending ratio of regular coffee samples by information technology

Osamu Tominaga, Fumio Ito, Taizo Hanai, Hiroyuki Honda, Takeshi Kobayashi

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

A searching method for the blending ratio of regular coffee with a designed flavor and taste has been developed. A fuzzy neural network (FNN) model was at first constructed for estimation of the sensory scores of various blending ratios. Using the model, the following four methods were attempted in order to estimate the blending ratio with the designed sensory score: 1) an exhaustive search, 2) a method using a genetic algorithm (GA), 3) a method using the GA combined with a reliability index (RIGA), and 4) a reverse FNN model. Among the results of these methods, the RIGA showed a good performance not only on estimation of the known blending ratio but also on the actual blending test in the present study.

Original language	English
Pages (from-to)	137-143
Number of pages	7
Journal	JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
Volume	35
Issue number	2
DOIs	https://doi.org/10.1252/jcej.35.137
Publication status	Published - Feb 2002
Externally published	Yes

All Science Journal Classification (ASJC) codes

Chemistry(all)
Chemical Engineering(all)

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abstract = "A searching method for the blending ratio of regular coffee with a designed flavor and taste has been developed. A fuzzy neural network (FNN) model was at first constructed for estimation of the sensory scores of various blending ratios. Using the model, the following four methods were attempted in order to estimate the blending ratio with the designed sensory score: 1) an exhaustive search, 2) a method using a genetic algorithm (GA), 3) a method using the GA combined with a reliability index (RIGA), and 4) a reverse FNN model. Among the results of these methods, the RIGA showed a good performance not only on estimation of the known blending ratio but also on the actual blending test in the present study.",

author = "Osamu Tominaga and Fumio Ito and Taizo Hanai and Hiroyuki Honda and Takeshi Kobayashi",

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T1 - Determination of the blending ratio of regular coffee samples by information technology

AU - Tominaga, Osamu

AU - Ito, Fumio

AU - Hanai, Taizo

AU - Honda, Hiroyuki

AU - Kobayashi, Takeshi

PY - 2002/2

Y1 - 2002/2

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AB - A searching method for the blending ratio of regular coffee with a designed flavor and taste has been developed. A fuzzy neural network (FNN) model was at first constructed for estimation of the sensory scores of various blending ratios. Using the model, the following four methods were attempted in order to estimate the blending ratio with the designed sensory score: 1) an exhaustive search, 2) a method using a genetic algorithm (GA), 3) a method using the GA combined with a reliability index (RIGA), and 4) a reverse FNN model. Among the results of these methods, the RIGA showed a good performance not only on estimation of the known blending ratio but also on the actual blending test in the present study.

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Determination of the blending ratio of regular coffee samples by information technology

Abstract

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