Sensors 2012, 12(12), 16262-16273; doi:10.3390/s121216262

Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays

1email, 1email, 1email, 1email, 1email, 2email and 1,* email
Received: 20 September 2012; in revised form: 15 November 2012 / Accepted: 19 November 2012 / Published: 23 November 2012
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Abstract: This paper presents a new pattern recognition approach for enhancing the selectivity of gas sensor arrays for clustering intelligent odor detection. The aim of this approach was to accurately classify an odor using pattern recognition in order to enhance the selectivity of gas sensor arrays. This was achieved using an odor monitoring system with a newly developed neural-genetic classification algorithm (NGCA). The system shows the enhancement in the sensitivity of the detected gas. Experiments showed that the proposed NGCA delivered better performance than the previous genetic algorithm (GA) and artificial neural networks (ANN) methods. We also used PCA for data visualization. Our proposed system can enhance the reproducibility, reliability, and selectivity of odor sensor output, so it is expected to be applicable to diverse environmental problems including air pollution, and monitor the air quality of clean-air required buildings such as a kindergartens and hospitals.
Keywords: gas sensor array; odor monitoring; pattern recognition; artificial neural networks (ANN); genetic algorithm (GA); neural-genetic classification algorithm (NGCA)
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MDPI and ACS Style

Kim, E.; Lee, S.; Kim, J.H.; Kim, C.; Byun, Y.T.; Kim, H.S.; Lee, T. Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays. Sensors 2012, 12, 16262-16273.

AMA Style

Kim E, Lee S, Kim JH, Kim C, Byun YT, Kim HS, Lee T. Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays. Sensors. 2012; 12(12):16262-16273.

Chicago/Turabian Style

Kim, Eungyeong; Lee, Seok; Kim, Jae H.; Kim, Chulki; Byun, Young T.; Kim, Hyung S.; Lee, Taikjin. 2012. "Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays." Sensors 12, no. 12: 16262-16273.

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