Abstract
This paper considers a new construction of an electronic nose system based on a neural network. The neural network used here is a competitive neural network by the learning vector quantization. Various odors are measured with an array of many metal oxide gas sensors. After reducing noises from the odor data which are measured under the different concentrations, we take the maximum values among the time series data of odors. They are affected by concentration levels, we use a normalization method to reduce the fluctuation of the data due to the concentration levels. Those data are used to classify the various odors of teas and coffees. The accuracy of the classification is around 96% in case of four kinds of teas and around 89% for five kinds of coffees.
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Omatu, S., Yano, M. (2014). E-Nose System by Using Neural Networks. In: Omatu, S., Bersini, H., Corchado, J., RodrÃguez, S., Pawlewski, P., Bucciarelli, E. (eds) Distributed Computing and Artificial Intelligence, 11th International Conference. Advances in Intelligent Systems and Computing, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-319-07593-8_36
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DOI: https://doi.org/10.1007/978-3-319-07593-8_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07592-1
Online ISBN: 978-3-319-07593-8
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