کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
625203 1455419 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Study of dead-end microfiltration features in sequencing batch reactor (SBR) by optimized neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تصفیه و جداسازی
پیش نمایش صفحه اول مقاله
Study of dead-end microfiltration features in sequencing batch reactor (SBR) by optimized neural networks
چکیده انگلیسی

In this research, the structure optimized BP-ANN model was applied to simulate the permeate flux as a function of mixed liquor suspended, temperature, dissolved oxygen, hydraulic retention time, transmembrane pressure and operating time during dead-end microfiltration of activated sludge suspensions and its supernatant from sequencing batch reactor (SBR). This artificial neural network approach was also used to model the chemical oxygen demand (COD) concentration of effluent from SBR. The results showed that the structure optimized single hidden layer neural networks was able to accurately simulate the dynamic behavior of permeate flux and the COD concentration for SBR activated sludge process, and this BP-ANN model possessed higher accuracy than that of C. M. Silva's predictive model and linear multi-regression model.

Research highlights
► Optimal topology configuration of ANN was used to predict the MFM flux from MBR.
► Optimal topology configuration of ANN was used to predict supernatant's COD from MBR.
► The predicted result of ANN is better than that of M. Silva's and regression models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Desalination - Volume 272, Issues 1–3, 3 May 2011, Pages 27–35
نویسندگان
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