QCM Sensor-Based Alcohol Classification by Advance Machine Learning Approach-Reference-Cited by-同舟云学术

QCM Sensor-Based Alcohol Classification by Advance Machine Learning Approach

Published:2021 Issue: Volume: Page:305-320
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Rao B. Kameswara,Kumar P. Suresh,Reddy Dukka Karun Kumar,Nayak Janmenjoy,Naik Bighnaraj

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-8439-8_25

Reference21 articles.

1. Di Nucci C et al (2003) A measurement system for odor classification based on the dynamic response of QCM sensors. IEEE Trans Instrum Meas 52(4):1079–1086

2. Leung YC, Yip DHF, Yu WWH (1997) An analogue ANN for classification of alcohol. In: 1997 IEEE international conference on systems, man, and cybernetics. Computational cybernetics and simulation, vol 4, no. 852, pp 4010–4015

3. Li Q, Gu Y, Wang N (2017) Application of random forest classifier by means of a QCM-based E-nose in the identification of Chinese liquor flavors. IEEE Sens J 17(6):1788–1794

4. Adak MF, Lieberzeit P, Jarujamrus P, Yumusak N (2019) Classification of alcohols obtained by QCM sensors with different characteristics using ABC based neural network. Eng Sci Technol Int J. https://doi.org/10.1016/j.jestch.2019.06.011.

5. Ordukaya E, Karlik B (2016) Fruit juice-alcohol mixture analysis using machine learning and electronic nose. IEE J Trans Electr Electron Eng 11(July):S171–S176

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