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
相关论文
共 50 条
  • [21] Artificial Neural Networks in the Problem of Classification of Defects of Electronic Devices
    K. I. Pham Le Quoc Han
    A. S. Bushmeleva
    S. U. Uvaysova
    Journal of Communications Technology and Electronics, 2021, 66 : 1068 - 1074
  • [22] Artificial Neural Networks in the Problem of Classification of Defects of Electronic Devices
    Han, Pham Le Quoc
    Bushmeleva, K. I.
    Uvaysova, A. S.
    Uvaysov, S. U.
    JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS, 2021, 66 (09) : 1068 - 1074
  • [23] Classification of Road Objects using Convolutional Neural Networks
    Patel, Mann
    Elgazzar, Heba
    2023 IEEE 13TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE, CCWC, 2023, : 326 - 332
  • [24] Development of an Electronic Nose for Smell Categorization Using Artificial Neural Network
    Macasaet, Dailyne
    Bandala, Argel
    Illahi, Ana Antoniette
    Dadios, Elmer
    Lauguico, Sandy
    Alejandrino, Jonnel
    JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, 2021, 12 (01) : 36 - 44
  • [25] Estimating Gas Concentration using Artificial Neural Network for Electronic Nose
    Sabilla, Shoffi Izza
    Sarno, Riyanarto
    Siswantoro, Joko
    4TH INFORMATION SYSTEMS INTERNATIONAL CONFERENCE (ISICO 2017), 2017, 124 : 181 - 188
  • [26] Prediction of Rice Odor by Using an Electronic Nose and Artificial Neural Network
    Aunsa-Ard, Wandee
    Earnsa-ard, Tanthip
    Pobkrut, Theerapat
    Kerdcharoen, Teerakiat
    2019 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW), 2019,
  • [27] Classification of Ear, Nose, and Throat Bacteria Using a Neural-Network-Based Electronic Nose
    Ritaban Dutta
    Julian W. Gardner
    Evor L. Hines
    MRS Bulletin, 2004, 29 : 709 - 713
  • [28] Classification of ear, nose, and throat bacteria using a neural-network-based electronic nose
    Dutta, R
    Gardner, JW
    Hines, EL
    MRS BULLETIN, 2004, 29 (10) : 709 - 713
  • [29] Classification model in different forest strata in a floodplain environment using artificial neural networks
    Silva, Anthoinny Vittoria dos Santos
    de Souza, Rodrigo Galvao Teixeira
    Liarte, Gabriel Victor Caetano Carvalho
    Pinho, Bianca Caterine Piedade
    de Oliveira, Cinthia Pereira
    Gonzales, Duberli Geomar Elera
    de Lima, Robson Borges
    de Abreu, Jadson Coelho
    REVISTA FORESTAL MESOAMERICA KURU-RFMK, 2022, 19 (45): : 64 - 70
  • [30] Using artificial neural networks to assess the applicability of recycled aggregate classification by different specifications
    Duan, Zhenhua
    Poon, Chi Sun
    Xiao, Jianzhuang
    MATERIALS AND STRUCTURES, 2017, 50 (02)
12345