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AuthorAkbar, Muhammad Ali
AuthorAli, Amine Ait Si
AuthorAmira, Abbes
AuthorBensaali, Faycal
AuthorBenammar, Mohieddine Amor
AuthorHassan, Muhammad
AuthorBermak, Amine
Available date2022-12-29T07:34:42Z
Publication Date2015
Publication NameARPN Journal of Engineering and Applied Sciences
ResourceScopus
URIhttp://hdl.handle.net/10576/37808
AbstractTin-oxide based gas sensor requires an operating temperature typically in the range of 200 °C to 400 °C and its performance dependents on this temperature. In this paper a deep examination has been made to analyze the best operating temperature suitable for gas identification application in which an array of sensors is used along with an appropriate feature reduction algorithm. The two most common feature reduction algorithms for gas classification are principal component analysis (PCA) and linear discriminant analysis (LDA); both of them have been used in this analytical work. The feature reduction is followed by a binary decision tree (BDT) or K-nearest neighbor (KNN) based classifier. Results obtained with data from an array of sensors used for detecting C6H6, CH2O, CO, NO2 and SO2 indicates that at 400 °C the BDT can classify 100% of gases after LDA based feature reduction, whereas KNN can classify 100% of gases at 200 °C and 300 °C using data before and after feature reduction. Furthermore, experimental results from the given sensor data suggest that with and without considering the operating temperature the BDT can classify 96% of gases using first four LDA components. While KNN can classify 98% to 99% of gases using first four LDA or first five PCA components of resulting data obtained after feature reduction. Thus, after LDA-based feature reduction both classifiers provide superior identification with minimum number of components. 2006-2015 Asian Research Publishing Network (ARPN).
Languageen
PublisherAsian Research Publishing Network
SubjectElectronic nose
Feature reduction
Gas identification
Sensor array
TitleImpact of feature reduction and operating temperature on gas identification
TypeArticle
Pagination8783-8790
Issue Number19
Volume Number10
dc.accessType Abstract Only


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