Portable Electronic Nose System for Identification of Synthesized Gasoline Using Metal Oxide Gas Sensor and Pattern Recognition
| Autor: | Young Wung Kim, Hong Bae Park, In Soo Lee, Jung Hwan Cho, Perena Gouma |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Engineering
Artificial neural network Electronic nose business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Fuzzy logic Microcontroller ComputingMethodologies_PATTERNRECOGNITION Multilayer perceptron Pattern recognition (psychology) Artificial intelligence Gasoline business Test data |
| Zdroj: | AIP Conference Proceedings. |
| ISSN: | 0094-243X |
| DOI: | 10.1063/1.3626326 |
| Popis: | This paper describes a portable electronic nose (e‐nose) system for use in the identification of synthesized gasoline, comprised of a single semiconductor type of gas sensor and pattern recognition neural networks. The designed e‐nose system consists of a one‐chip microcontroller, a pre‐concentrator, and a gas sensor. Two different neural networks, a multilayer perceptron (MLP) neural network and a fuzzy ARTMAP neural network were applied to discriminate synthesized gasoline from normal gasoline. The results of the classification showed 100% and 85% recognition rates for the training data set and testing data set, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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