Farkli sensörlerle yanici gazlarin ölçülmesi ve dinamik modellenmesi

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dc.authorscopusid57211714933
dc.authorscopusid57211713895
dc.authorscopusid57211713157
dc.authorscopusid57211712318
dc.authorscopusid57196895937
dc.contributor.authorKircil O.
dc.contributor.authorAnmaz S.
dc.contributor.authorMafratoglu B.
dc.contributor.authorBabaoglan H.
dc.contributor.authorAtes A.
dc.date.accessioned2024-08-04T20:03:57Z
dc.date.available2024-08-04T20:03:57Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description2019 International Conference on Artificial Intelligence and Data Processing Symposium, IDAP 2019 -- 21 September 2019 through 22 September 2019 -- 153040en_US
dc.description.abstractIn this study, lighter gases was measured with different sensors. Measurements were performed under the normal room condition according to different sampling intervals. Data sets were modeled with Matlab system identification toolbox. Generated nonlinear dynamic model was used for making prediction for gas evolution. With this study, early warning system can be proposed by generating gas evaluation models were used for some dangerous gases such as butane, methane. © 2019 IEEE.en_US
dc.identifier.doi10.1109/IDAP.2019.8875962
dc.identifier.isbn9781728129327
dc.identifier.scopus2-s2.0-85074877580en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/IDAP.2019.8875962
dc.identifier.urihttps://hdl.handle.net/11616/92237
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2019 International Conference on Artificial Intelligence and Data Processing Symposium, IDAP 2019en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdynamic system modelingen_US
dc.subjectgas detectionen_US
dc.subjectmodelingen_US
dc.titleFarkli sensörlerle yanici gazlarin ölçülmesi ve dinamik modellenmesien_US
dc.typeConference Objecten_US

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