Sabilla, Shoffi Izza and Sarno, Riyanarto and Siswantoro, Joko (2017) Estimating Gas Concentration using Artificial Neural Network for Electronic Nose. Procedia Computer Science, 124. pp. 181-188. ISSN 1877-0509
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Abstract
E-nose is a sensor used to detect the existence of gas in the air. Some types of sensor has the ability to detect certain gas and also has different datasheet. Slope deflection is the method to determine the suitable sensor for the experiment. E-nose with MQ Family produces the ratio of existing air and base line air resistance, and it is usually equipped with a datasheet containing the consecration of detected gas in a certain value of the sensor to convert the output to the concentration of detected gas. The ratio is used to estimate the concentration of a gas. In this paper, Artificial neural network is used to estimate the concentration of a gas in the air based on the ratio. Providing the accurate calculation of the ratio is very important to increase the Electronic nose performance, and the result of this experiment showed that the Artificial neural network method achieves a good performance with smaller RMSE of 0.0433 compared with the existing methods.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Artifical Neural Network, Sensor, Electronic Nose, Mangoes Ripenes |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering > Department of Informatic |
| Depositing User: | Joko Siswantoro |
| Date Deposited: | 29 Jul 2020 05:40 |
| Last Modified: | 24 Mar 2021 16:25 |
| URI: | http://repository.ubaya.ac.id/id/eprint/37946 |
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