Nyayu, Latifah Husni and Handayani, Ade Silvia and Nurmaini, Siti and Yani, Irsyadi (2017) Odor Classification Using Support Vector Machine. International Conference on Electrical Engineering and Computer Science (ICECOS).
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Abstract
This paper discusses about the process of classifying odor using Support Vector Machine. The training data was taken using a robot that ran in indoor room. The odor was sensed by 3 gas sensors, namely: TGS 2600, TGS 2602, and TGS 2620. The experimental environment was controlled and conditioned. The temperature was kept between 27.5 0C to 30.5 0C and humidity was in the range of 65% -75 %. After simulation testing in Matlab, the classification was then done in real experiment using one versus others technique. The result shows that the classification can be achieved using simulation and real experiment.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | odor; SVM; classification; TGS |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Electrical Engineering > Misc |
| Depositing User: | Mrs Trisni Handayani |
| Date Deposited: | 25 Mar 2022 03:49 |
| Last Modified: | 27 Oct 2022 07:51 |
| URI: | http://eprints.polsri.ac.id/id/eprint/11118 |
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