Matches in SemOpenAlex for { <https://semopenalex.org/work/W2023252777> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W2023252777 endingPage "7" @default.
- W2023252777 startingPage "1" @default.
- W2023252777 abstract "A Wiener-Laguerre model with artificial neural network (ANN) as its nonlinear static part was employed to describe the dynamic behavior of a sequencing batch reactor (SBR) used for the treatment of dye-containing wastewater. The model was developed based on the experimental data obtained from the treatment of an effluent containing a reactive textile azo dye, Cibacron yellow FN-2R, by Sphingomonas paucimobilis bacterium. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mi>α</mml:mi><mml:mo>=</mml:mo><mml:mn>0.44</mml:mn></mml:math>. In order to adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:msup><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mo>></mml:mo><mml:mn>0.99</mml:mn></mml:math>and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics." @default.
- W2023252777 created "2016-06-24" @default.
- W2023252777 creator A5012865471 @default.
- W2023252777 creator A5034472524 @default.
- W2023252777 creator A5059076374 @default.
- W2023252777 creator A5072652336 @default.
- W2023252777 creator A5078040199 @default.
- W2023252777 creator A5091893323 @default.
- W2023252777 date "2014-01-01" @default.
- W2023252777 modified "2023-10-17" @default.
- W2023252777 title "Long-Term Prediction of Biological Wastewater Treatment Process Behavior via Wiener-Laguerre Network Model" @default.
- W2023252777 cites W137291291 @default.
- W2023252777 cites W1967429206 @default.
- W2023252777 cites W1983024735 @default.
- W2023252777 cites W1990140330 @default.
- W2023252777 cites W2000812593 @default.
- W2023252777 cites W2002793881 @default.
- W2023252777 cites W2004744718 @default.
- W2023252777 cites W2005099579 @default.
- W2023252777 cites W2015645066 @default.
- W2023252777 cites W2025299343 @default.
- W2023252777 cites W2025738966 @default.
- W2023252777 cites W2025798936 @default.
- W2023252777 cites W2035335541 @default.
- W2023252777 cites W2042728365 @default.
- W2023252777 cites W2043900664 @default.
- W2023252777 cites W2053224328 @default.
- W2023252777 cites W2054326723 @default.
- W2023252777 cites W2055337535 @default.
- W2023252777 cites W2069321559 @default.
- W2023252777 cites W2071214038 @default.
- W2023252777 cites W2078475310 @default.
- W2023252777 cites W2087460167 @default.
- W2023252777 cites W2093353308 @default.
- W2023252777 cites W2103667821 @default.
- W2023252777 cites W2118387928 @default.
- W2023252777 cites W2162548023 @default.
- W2023252777 doi "https://doi.org/10.1155/2014/248450" @default.
- W2023252777 hasPublicationYear "2014" @default.
- W2023252777 type Work @default.
- W2023252777 sameAs 2023252777 @default.
- W2023252777 citedByCount "8" @default.
- W2023252777 countsByYear W20232527772015 @default.
- W2023252777 countsByYear W20232527772017 @default.
- W2023252777 countsByYear W20232527772019 @default.
- W2023252777 countsByYear W20232527772020 @default.
- W2023252777 crossrefType "journal-article" @default.
- W2023252777 hasAuthorship W2023252777A5012865471 @default.
- W2023252777 hasAuthorship W2023252777A5034472524 @default.
- W2023252777 hasAuthorship W2023252777A5059076374 @default.
- W2023252777 hasAuthorship W2023252777A5072652336 @default.
- W2023252777 hasAuthorship W2023252777A5078040199 @default.
- W2023252777 hasAuthorship W2023252777A5091893323 @default.
- W2023252777 hasBestOaLocation W20232527771 @default.
- W2023252777 hasConcept C11413529 @default.
- W2023252777 hasConcept C147455438 @default.
- W2023252777 hasConcept C167085575 @default.
- W2023252777 hasConcept C185592680 @default.
- W2023252777 hasConcept C192562407 @default.
- W2023252777 hasConcept C39432304 @default.
- W2023252777 hasConcept C41008148 @default.
- W2023252777 hasConcept C87717796 @default.
- W2023252777 hasConcept C94061648 @default.
- W2023252777 hasConceptScore W2023252777C11413529 @default.
- W2023252777 hasConceptScore W2023252777C147455438 @default.
- W2023252777 hasConceptScore W2023252777C167085575 @default.
- W2023252777 hasConceptScore W2023252777C185592680 @default.
- W2023252777 hasConceptScore W2023252777C192562407 @default.
- W2023252777 hasConceptScore W2023252777C39432304 @default.
- W2023252777 hasConceptScore W2023252777C41008148 @default.
- W2023252777 hasConceptScore W2023252777C87717796 @default.
- W2023252777 hasConceptScore W2023252777C94061648 @default.
- W2023252777 hasLocation W20232527771 @default.
- W2023252777 hasOpenAccess W2023252777 @default.
- W2023252777 hasPrimaryLocation W20232527771 @default.
- W2023252777 hasRelatedWork W1977384357 @default.
- W2023252777 hasRelatedWork W2387081153 @default.
- W2023252777 hasRelatedWork W2611934430 @default.
- W2023252777 hasRelatedWork W2748952813 @default.
- W2023252777 hasRelatedWork W2841594860 @default.
- W2023252777 hasRelatedWork W2891503706 @default.
- W2023252777 hasRelatedWork W2895399064 @default.
- W2023252777 hasRelatedWork W2899084033 @default.
- W2023252777 hasRelatedWork W3008141799 @default.
- W2023252777 hasRelatedWork W3092014128 @default.
- W2023252777 hasVolume "2014" @default.
- W2023252777 isParatext "false" @default.
- W2023252777 isRetracted "false" @default.
- W2023252777 magId "2023252777" @default.
- W2023252777 workType "article" @default.