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Mixed Odor Classification for QCM Sensor Data by Neural Networks

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Distributed Computing and Artificial Intelligence

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 151))

Abstract

Compared with metal oxide semiconductor gas sensors, quarts crystal microbalance (QCM) sensors are sensitive for odors. Using an array of QCM sensors, we measure mixed odors and classify them into an original odor class before mixing based on neural networks. For simplicity we consider the case that two kinds of odor are mixed since more than two becomes too complex to analize the classification results. We have used eight sensors and four kinds of odor are used as the original odors. The neural network used here is a conventional layered neural network. The classification is acceptable although the perfect classification could not been achieved.

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References

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Osaka Institute of Technology, 5-16-1 Omiya Asahi-ku, Osaka, 535-8585, Japan

    Sigeru Omatu

  2. Faculty of Information Science and Technology, Osaka Institute of Technology, 1-79-1 Kitayama, Hirakata, 573-0196, Japan

    Hideo Araki

  3. Faculty of Education, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, 599-8531, Japan

    Toru Fujinaka

  4. Faculty of Engineering, Osaka Prefecture University, 1-1 Gakuencho Nakaku, Sakai, 599-8531, Japan

    Michifumi Yoshioka

  5. Faculty of Engineering, Osaka Prefecture University, 1-1 Gakuencho Nakaku, Sakai, 739-8524, Japan

    Hiroyuki Nakazumi

Authors
  1. Sigeru Omatu
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  2. Hideo Araki
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  3. Toru Fujinaka
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  4. Michifumi Yoshioka
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  5. Hiroyuki Nakazumi
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Corresponding author

Correspondence to Sigeru Omatu .

Editor information

Editors and Affiliations

  1. Dept. Computer Science &, Intelligent Systems, Osaka Prefecture University, Gakuen-chu 1-1, Sakai, Osaka, 599-8531, Japan

    Sigeru Omatu

  2. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan F. De Paz Santana

  3. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Sara Rodríguez González

  4. Escuela Politécnica Superior (EPS), Depto. Informática, Universidad Carlos III de Madrid, Avenida de la Universidad Carloss III 22, Madrid, 28270, Spain

    Jose M. Molina

  5. , Data Processing and Simulation Group, Universidad Politécnica de Madrid, Calle de Ramiro de Maeztu, 7, Madrid, 28040, Spain

    Ana M. Bernardos

  6. Faculty of Science, Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan M. Corchado Rodríguez

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© 2012 Springer-Verlag Berlin Heidelberg

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Omatu, S., Araki, H., Fujinaka, T., Yoshioka, M., Nakazumi, H. (2012). Mixed Odor Classification for QCM Sensor Data by Neural Networks. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., Rodríguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_1

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  • DOI: https://doi.org/10.1007/978-3-642-28765-7_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28764-0

  • Online ISBN: 978-3-642-28765-7

  • eBook Packages: EngineeringEngineering (R0)

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