Neural network based electronic nose for apple ripeness determination
UNSPECIFIED. (1999) Neural network based electronic nose for apple ripeness determination. ELECTRONICS LETTERS, 35 (10). pp. 821-823. ISSN 0013-5194Full text not available from this repository.
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|
|Date:||13 May 1999|
|Number of Pages:||3|
|Page Range:||pp. 821-823|
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