Quantitative information extraction from gas sensor data using principal component regression

Özmen, Ahmet; Bekir Mumyakmaz; Mehmet Ali Ebeoglu; Cihat Tasaltin; Ilke Gurol; Zafer Ziya Ozturk; Balta, Deniz

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dc.date.accessioned	2020-01-13T09:08:45Z
dc.date.available	2020-01-13T09:08:45Z
dc.date.issued	2016
dc.identifier.citation	Ozmen, A; Mumyakmaz, B; Ebeoglu, MA; Tasaltin, C; Gurol, I; Ozturk, ZZ; Dural, D; (2016). Quantitative information extraction from gas sensor data using principal component regression. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 24, 960-946
dc.identifier.issn	1300-0632
dc.identifier.uri	https://hdl.handle.net/20.500.12619/2624
dc.identifier.uri	https://doi.org/10.3906/elk-1309-96
dc.description.abstract	Several experiments are conducted using two industrial gases (toluene and ethanol) to validate the approach. The new approach is also compared with two classic principal component regression (PCR) methods. The results show that the new approach performs better than the classic PCR approaches.
dc.language	English
dc.publisher	TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY
dc.subject	Engineering
dc.title	Quantitative information extraction from gas sensor data using principal component regression
dc.type	Article
dc.identifier.volume	24
dc.identifier.startpage	946
dc.identifier.endpage	960
dc.contributor.department	Sakarya Üniversitesi/Bilgisayar Ve Bilişim Bilimleri Fakültesi/Yazılım Mühendisliği Bölümü
dc.contributor.saüauthor	Özmen, Ahmet
dc.contributor.saüauthor	Balta, Deniz
dc.relation.journal	TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
dc.identifier.wos	WOS:000374121500018
dc.identifier.doi	10.3906/elk-1309-96
dc.identifier.eissn	1303-6203
dc.contributor.author	Özmen, Ahmet
dc.contributor.author	Bekir Mumyakmaz
dc.contributor.author	Mehmet Ali Ebeoglu
dc.contributor.author	Cihat Tasaltin
dc.contributor.author	Ilke Gurol
dc.contributor.author	Zafer Ziya Ozturk
dc.contributor.author	Balta, Deniz