2007
DOI: 10.1007/s00477-007-0191-5
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Stochastic modeling applications for the prediction of COD removal efficiency of UASB reactors treating diluted real cotton textile wastewater

Abstract: A three-layer Artificial Neural Network (ANN) model (9:12:1) for the prediction of Chemical Oxygen Demand Removal Efficiency (CODRE) of Upflow Anaerobic Sludge Blanket (UASB) reactors treating real cotton textile wastewater diluted with domestic wastewater was presented. To validate the proposed method, an experimental study was carried out in three lab-scale UASB reactors to investigate the treatment efficiency on total COD reduction. The reactors were operated for 80 days at mesophilic conditions (36-37.5°C)… Show more

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Cited by 57 publications
(38 citation statements)
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“…For comparative purpose, the measured data were evaluated by a multiple regression software package (DataFit® V8.1.69, Copyright© 1995, Oakdale Engineering, PA, RC167), containing 298 two-dimensional (2D) and 242 three-dimensional (3D) non-linear regression models. The regression analysis was performed based on the Levenberg-Marquardt method with double precision, as similarly done in several studies of the first author (Yetilmezsoy, 2007;Yetilmezsoy and Saral, 2007;Yetilmezsoy and Sapci-Zengin, 2009;Yetilmezsoy and Sakar, 2008;Turkdogan-Aydinol and Yetilmezsoy, 2010;Yetilmezsoy, 2011;Yetilmezsoy, 2012).…”
Section: Multiple Regression-based Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…For comparative purpose, the measured data were evaluated by a multiple regression software package (DataFit® V8.1.69, Copyright© 1995, Oakdale Engineering, PA, RC167), containing 298 two-dimensional (2D) and 242 three-dimensional (3D) non-linear regression models. The regression analysis was performed based on the Levenberg-Marquardt method with double precision, as similarly done in several studies of the first author (Yetilmezsoy, 2007;Yetilmezsoy and Saral, 2007;Yetilmezsoy and Sapci-Zengin, 2009;Yetilmezsoy and Sakar, 2008;Turkdogan-Aydinol and Yetilmezsoy, 2010;Yetilmezsoy, 2011;Yetilmezsoy, 2012).…”
Section: Multiple Regression-based Modelmentioning
confidence: 99%
“…Although statistical models may be able to establish a relationship between the input and the output variables without detailing the causes and effects in the formation of pollutants, however, they are not capable of capturing the inherent non-linear nature of the problem and forecasting short-term pollution levels (Agirre-Basurko et al, 2006;Barai et al, 2007;Akkoyunlu et al, 2010). Since the number of meteorological and pollution parameters implies highdimensional input space and high computational capacity, it is believed that artificial intelligence-based techniques may provide a good alternative to traditional techniques due to their speed, robustness and non-linear characteristics (Yetilmezsoy and Sapci-Zengin, 2009;Akkoyunlu et al, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…Deterministic models also provide a good insight into the mechanism of biological relationships, but fluctuation of kinetic parameters and wastewater characteristics normally results in a laborious calibration, comprehensive computer analysis as well as laboratory work [14]. The International Water Association (IWA) Anaerobic Digestion Model No.1 (ADM1), a typical deterministic model, has been successfully used for modeling the whole anaerobic digestion process [19].…”
Section: Introductionmentioning
confidence: 99%
“…Other reports also confirmed that process modeling based on previously acquired data is one technical route to enhancing the performance of anaerobic processes. These process models are often developed [14,15]. Nonetheless, modeling of anaerobic digestion is quite challenging and tough because performance of anaerobic systems is complex and varies considerably with influent characteristics and operational conditions [16].…”
mentioning
confidence: 99%
“…The substrate composition and organic loading rate on the process performance during start-up and steady state were studied by N. Musee (2007) [6] , Kaan Yetilmezsoy (2009) [7] Matsumoto and Noike (1991) [8] . The optimum values of operating variables for treating hog wastewater were reported (Chen et al, 1997) [9] for the anaerobic fluidized bed treatment of hog wastewater. The feasibility of treatment of monosodium glutamate fermentation wastewater was evaluated (Tseng and Lin, 1990) [10] in terms of removal efficiency and methane content in the biogas.…”
Section: Introductionmentioning
confidence: 99%