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Quantitative information extraction from gas sensor data using principal component regression

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dc.contributor.authors Ozmen, A; Mumyakmaz, B; Ebeoglu, MA; Tasaltin, C; Gurol, I; Ozturk, ZZ; Dural, D;
dc.date.accessioned 2020-01-13T07:57:00Z
dc.date.available 2020-01-13T07:57:00Z
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/20.500.12619/2452
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


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