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Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.

Miao J, Zhang T, Wang Y, Li G - Sensors (Basel) (2015)

Bottom Line: The relation of the minimum numbers of sensors with number of samples in the sample set was revealed.The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually.Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. jiacheng@zju.edu.cn.

ABSTRACT
The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

No MeSH data available.


Example of responses of 12 sensors to ginseng sample.
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sensors-15-16027-f002: Example of responses of 12 sensors to ginseng sample.

Mentions: The gas chamber was washed with a clean-air flow of 1 L/min for 360 s to allow the sensors to return to the baseline before another new cycle of measurements. Then the clean-air flow was turned off and the target gas was quickly injected into the chamber with a syringe. The response of sensors was collected for 180 s, and then the clean-air flow was turned on to wash away the target gas. The response of 12 sensors was recorded for 340 s at 2 Hz during each testing, including 20 s before and 140 s after the measurement response of sensors, as shown in Figure 2. A total of 315 samples, 35 for each species, were obtained. The experiment was conducted at room temperature (20–25 °C) and humidity of 50%–70%. During one measurement (which usually takes 10–15 min), the temperature and humidity of ambient environment were relatively stable.


Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.

Miao J, Zhang T, Wang Y, Li G - Sensors (Basel) (2015)

Example of responses of 12 sensors to ginseng sample.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541866&req=5

sensors-15-16027-f002: Example of responses of 12 sensors to ginseng sample.
Mentions: The gas chamber was washed with a clean-air flow of 1 L/min for 360 s to allow the sensors to return to the baseline before another new cycle of measurements. Then the clean-air flow was turned off and the target gas was quickly injected into the chamber with a syringe. The response of sensors was collected for 180 s, and then the clean-air flow was turned on to wash away the target gas. The response of 12 sensors was recorded for 340 s at 2 Hz during each testing, including 20 s before and 140 s after the measurement response of sensors, as shown in Figure 2. A total of 315 samples, 35 for each species, were obtained. The experiment was conducted at room temperature (20–25 °C) and humidity of 50%–70%. During one measurement (which usually takes 10–15 min), the temperature and humidity of ambient environment were relatively stable.

Bottom Line: The relation of the minimum numbers of sensors with number of samples in the sample set was revealed.The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually.Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. jiacheng@zju.edu.cn.

ABSTRACT
The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

No MeSH data available.