Mining Data of Noisy Signal Patterns in Recognition of Gasoline Bio-Based Additives using Electronic Nose

Mining Data of Noisy Signal Patterns in Recognition of Gasoline Bio-Based Additives using Electronic Nose

The paper analyses the distorted data of an electronic nose in recognizing the gasoline bio-based additives. Different tools of data mining, such as the methods of data clustering, principal component analysis, wavelet transformation, support vector machine and random forest of decision trees are ap...

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Bibliographic Details
Main Authors: Osowski Stanisław, Siwek Krzysztof
Format: Article
Language:English
Published: Polish Academy of Sciences 2017-03-01
Series:Metrology and Measurement Systems
Subjects:
data mining
electronic nose
gasoline blends
random forest
support vector machine
wavelet denoising
Online Access:http://www.degruyter.com/view/j/mms.2017.24.issue-1/mms-2017-0015/mms-2017-0015.xml?format=INT

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http://www.degruyter.com/view/j/mms.2017.24.issue-1/mms-2017-0015/mms-2017-0015.xml?format=INT

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