Regression model-based predictions of diel, diurnal and nocturnal dissolved oxygen dynamics after wavelet denoising of noisy time series

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dc.authorid0000-0002-0156-1657en_US
dc.authorid0000-0003-1099-4363en_US
dc.contributor.authorEvrendilek, Fatih
dc.contributor.authorKarakaya, Nusret
dc.date.accessioned2021-06-23T19:35:50Z
dc.date.available2021-06-23T19:35:50Z
dc.date.issued2014
dc.departmentBAİBÜ, Mühendislik Fakültesi, Çevre Mühendisliği Bölümüen_US
dc.description.abstractContinuous time-series measurements of diel dissolved oxygen (DO) through online sensors are vital to better understanding and management of metabolism of lake ecosystems, but are prone to noise. Discrete wavelet transforms (DWT) with the orthogonal Symmlet and the semiorthogonal Chui-Wang B-spline were compared in denoising diel, daytime and nighttime dynamics of DO, water temperature, pH, and chlorophyll-a. Predictive efficacies of multiple non-linear regression (MNLR) models of DO dynamics were evaluated with or without DWT denoising of either the response variable alone or all the response and explanatory variables. The combined use of the B-spline-based denoising of all the variables and the temporally partitioned data improved both the predictive power and the errors of the MNLR models better than the use of Symmlet DWF denois.ing of DO only or all the variables with or without the temporal partitioning. (C) 2014 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.physa.2014.02.062
dc.identifier.endpage15en_US
dc.identifier.issn0378-4371
dc.identifier.issn1873-2119
dc.identifier.scopus2-s2.0-84896794061en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage8en_US
dc.identifier.urihttps://doi.org/10.1016/j.physa.2014.02.062
dc.identifier.urihttps://hdl.handle.net/20.500.12491/7877
dc.identifier.volume404en_US
dc.identifier.wosWOS:000335638300002en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorEvrendilek, Fatih
dc.institutionauthorKarakaya, Nusret
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofPhysica A-Statistical Mechanics And Its Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectB-splinesen_US
dc.subjectDiscrete Wavelet Transformen_US
dc.subjectSymmletsen_US
dc.subjectTime Seriesen_US
dc.titleRegression model-based predictions of diel, diurnal and nocturnal dissolved oxygen dynamics after wavelet denoising of noisy time seriesen_US
dc.typeArticleen_US

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