Artificial Neural Network Modeling for Biological Removal of Organic Carbon and Nitrogen from Slaughterhouse Wastewater in a Sequencing Batch Reactor
المؤلفون المشاركون
Debsarkar, Anupam
Kundu, Pradyut
Mukherjee, Somnath
المصدر
Advances in Artificial Neural Systems
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-12-12
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
The present paper deals with treatment of slaughterhouse wastewater by conducting a laboratory scale sequencing batch reactor (SBR) with different input characterized samples, and the experimental results are explored for the formulation of feedforward backpropagation artificial neural network (ANN) to predict combined removal efficiency of chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N).
The reactor was operated under three different combinations of aerobic-anoxic sequence, namely, (4 + 4), (5 + 3), and (5 + 4) hour of total react period with influent COD and NH4+-N level of 2000 ± 100 mg/L and 120 ± 10 mg/L, respectively.
ANN modeling was carried out using neural network tools, with Levenberg-Marquardt training algorithm.
Various trials were examined for training of three types of ANN models (Models “A,” “B,” and “C”) using number of neurons in the hidden layer varying from 2 to 30.
All together 29, data sets were used for each three types of model for which 15 data sets were used for training, 7 data sets for validation, and 7 data sets for testing.
The experimental results were used for testing and validation of three types of ANN models.
Three ANN models (Models “A,” “B,” and “C”) were trained and tested reasonably well to predict COD and NH4+-N removal efficiently with 3.33% experimental error.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kundu, Pradyut& Debsarkar, Anupam& Mukherjee, Somnath. 2013. Artificial Neural Network Modeling for Biological Removal of Organic Carbon and Nitrogen from Slaughterhouse Wastewater in a Sequencing Batch Reactor. Advances in Artificial Neural Systems،Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-458887
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kundu, Pradyut…[et al.]. Artificial Neural Network Modeling for Biological Removal of Organic Carbon and Nitrogen from Slaughterhouse Wastewater in a Sequencing Batch Reactor. Advances in Artificial Neural Systems No. 2013 (2013), pp.1-15.
https://search.emarefa.net/detail/BIM-458887
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kundu, Pradyut& Debsarkar, Anupam& Mukherjee, Somnath. Artificial Neural Network Modeling for Biological Removal of Organic Carbon and Nitrogen from Slaughterhouse Wastewater in a Sequencing Batch Reactor. Advances in Artificial Neural Systems. 2013. Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-458887
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-458887
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر