Neural network based electronic nose for apple ripeness determination

被引：37

作者：

Hines, EL ^{[1
]}

Llobet, E

Gardner, JW

机构：

[1] Univ Warwick, Sch Engn, Div Elect & Elect Engn, Coventry CV4 7AL, W Midlands, England

[2] Univ Rovira & Virgili, Dept Elect Engn, Tarragona 43006, Spain

来源：

ELECTRONICS LETTERS | 1999年 / 35卷 / 10期

关键词：

D O I：

10.1049/el:19990547

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

It is possible to non-destructively determine apple ripeness using a simple electronic nose. The instrument employs tin oxide resistive gas sensors and neural networks (fuzzy ARTMAP, LVQ and MLP) to classify the samples into three states df ripeness with 100% accuracy. Fuzzy ARTMAP was found to be the best classifier in the presence of simulated Gaussian noise.

引用

页码：821 / 823

页数：3

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