Research of Electronic Nose Pattern Recognition Algorithm Based on SVM

Wei Liang; Li Na Zhang; Xiao Wei Li; Yan Di Zuo

doi:10.4028/www.scientific.net/AMM.220-223.2244

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223Research of Electronic Nose Pattern Recognition...

Research of Electronic Nose Pattern Recognition Algorithm Based on SVM

Abstract:

In order to improve the recognition rate of the electronic nose system for small samples, an electronic nose pattern recognition algorithm based on support vector machine (SVM) is proposed in this paper. Identification experiments for three kinds of wine with similar odor were carried out. The sensor arrays are optimized by means of principal component analysis (PCA) method first. Then, make comparing experiment using different algorithms for different number of training samples of wine. The related results show that PCA-SVM based pattern recognition algorithms has high recognition accuracy, stronger classification capability, and has potential advantages in small sample classification and recognition experiments.

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Periodical:

Applied Mechanics and Materials (Volumes 220-223)

Pages:

2244-2247

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.220-223.2244

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Online since:

November 2012

Authors:

Wei Liang, Li Na Zhang, Xiao Wei Li, Yan Di Zuo

Keywords:

Electronic Nose, Pattern Recognition, Support Vector

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References

[1] Cheng SM. Ma YJ.Zhou B.Research on the Tomato Seeds with Different Store Time and Different Blended Proportion by Using Electronic Nose [J]. Chinese Journal of Sensors and Actuators. 2011,24(7):941-945. [In Chinese]

Google Scholar

[2] Zhang HM. Wang J.Detection of Caffeine in Xinyangmaojian Tea by an Electronic Nose[J]. Chinese Journal of Sensors and Actuators.2011,24(8): 1223-1227. [In Chinese]

Google Scholar

[3] Pang LJ.Wang J.Discrimination of Aging Timing of Walnut by Electronic Nose Chinese journal of sensors and actuators[J]. Chinese Journal of Sensors and Actuators.2011,24(6):928-933. [In Chinese]

Google Scholar

[4] Wu LL. Huang PG.On Identifying Early Grains Mildewing based on Probabilistic Neural Network[J].Computer Application and Software. 2011,29(9):235-237. [In Chinese]

Google Scholar