Classification of Different Objects with Artificial Neural Networks Using Electronic Nose

被引：0
|
作者：
Ozsandikcioglu, Umit [1 ]
Atasoy, Ayten [1 ]
Guney, Selda [2 ]
机构：
[1] Karadeniz Tech Univ, Elekt Elekt Muhendisligi Bolumu, Trabzon, Turkey
[2] Baskent Univ, Elekt Elekt Muhendisligi Bolumu, Ankara, Turkey
来源：
2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年
关键词：
Electronic nose; Artificial Neural Networks; Classification;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper; an e-nose with low cost which consisting of 8 different gas sensors was used and with this e-nose 9 different odors ((mint, lemon, egg, rotten egg, angelica root, nail polish, naphthalene, rose water, and acetone) was classified. This 9 different odor are classified with Artificial Neural Networks and by using different activation functions, and then the successes of the classification were compared with each other. The maximum success of the testing data is obtained with 100% accuracy rate by using logsig activation function in hidden layer and tansig activation function in output layer. In conclusion; using the chemical database containing the odor of the different objects, distinct odors were shown to be classified correctly.
引用
收藏
页码：815 / 818
页数：4
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