Monitoring diel dissolved oxygen dynamics through integrating wavelet denoising and temporal neural networks

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dc.authorid0000-0003-1099-4363en_US
dc.authorid0000-0002-0156-1657en_US
dc.contributor.authorEvrendilek, Fatih
dc.contributor.authorKarakaya, Nusret
dc.date.accessioned2021-06-23T19:36:19Z
dc.date.available2021-06-23T19:36:19Z
dc.date.issued2014
dc.departmentBAİBÜ, Mühendislik Fakültesi, Çevre Mühendisliği Bölümüen_US
dc.description.abstractDiel dissolved oxygen (DO) time series measured continuously using proximal sensors in situ for a temperate lake were denoised using discrete wavelet transform (DWT) with the orthogonal wavelet families of coiflet, daubechies, and symmlet with order of 10. Diel DO time series denoised were modeled using nine temporal artificial neural networks (ANNs) as a function of water level, water temperature, electrical conductivity, pH, day of year, and hour. Our results showed that time-lag recurrent network (TLRN) using denoised data emulated diel DO dynamics better than the best-performing TLRN using the original data, time-delay neural network (TDNN), and recurrent network (RNN). Daubechies basis dealt with diel DO data slightly better than the other bases given its coefficient of determination (r (2) = 87.1 %), while symmlet performed slightly better than the other bases in terms of root mean square error (RMSE = 1.2 ppm) and mean absolute error (MAE = 0.9 ppm).en_US
dc.identifier.doi10.1007/s10661-013-3476-9
dc.identifier.endpage1591en_US
dc.identifier.issn0167-6369
dc.identifier.issn1573-2959
dc.identifier.issue3en_US
dc.identifier.pmid24100799en_US
dc.identifier.scopus2-s2.0-84895793454en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1583en_US
dc.identifier.urihttps://doi.org/10.1007/s10661-013-3476-9
dc.identifier.urihttps://hdl.handle.net/20.500.12491/7971
dc.identifier.volume186en_US
dc.identifier.wosWOS:000330715300021en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorEvrendilek, Fatih
dc.institutionauthorKarakaya, Nusret
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironmental Monitoring And Assessmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDiel Dynamicsen_US
dc.subjectDiscrete Wavelet Transformen_US
dc.subjectSurface Wateren_US
dc.subjectTime Seriesen_US
dc.titleMonitoring diel dissolved oxygen dynamics through integrating wavelet denoising and temporal neural networksen_US
dc.typeArticleen_US

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