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Neural network based electronic nose for apple ripeness determination
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UNSPECIFIED (1999) Neural network based electronic nose for apple ripeness determination. ELECTRONICS LETTERS, 35 (10). pp. 821-823. ISSN 0013-5194
Full text not available from this repository.Abstract
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.
| Item Type: | Journal Article |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Journal or Publication Title: | ELECTRONICS LETTERS |
| Publisher: | IEE-INST ELEC ENG |
| ISSN: | 0013-5194 |
| Date: | 13 May 1999 |
| Volume: | 35 |
| Number: | 10 |
| Number of Pages: | 3 |
| Page Range: | pp. 821-823 |
| Publication Status: | Published |
| URI: | http://wrap.warwick.ac.uk/id/eprint/14465 |
Data sourced from Thomson Reuters' Web of Knowledge
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