Effluent Quality Prediction of Wastewater Treatment System Based on Small-world ANN

نویسندگان

  • Ruicheng Zhang
  • Xulei Hu
چکیده

In order to provide a tool for predicting wastewater treatment performance and form a basis for controlling the operation of the process, a NW multi-layer forward small world artificial neural networks soft sensing model is proposed for the waste water treatment processes. The input and output variables of the network model were determined according to the waste water treatment system. The multi-layer forward small world artificial neural networks model was built, and the hidden layer structure of the network model was studied. The results of model calculation show that the predicted value can better match measured value, playing an effect of simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparisons of grey and neural network prediction of industrial park wastewater effluent using influent quality and online monitoring parameters.

In this study, Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids (SSeff) and chemical oxygen demand (CODeff) in the effluent from a wastewater treatment plant in industrial park of Taiwan. When constructing model or predicting, the influent quality or online monitoring parameters were adopted as the input variables. ANN was also adopted for comparison...

متن کامل

Dynamic Performance Analysis and Simulation of a Full Scale Activated Sludge System Treating an Industrial Wastewater Using Artificial Neural Network

Due to changeable nature of the industrial wastewaters, proper operation of an industrial wastewater treatment plant is of prior importance in order to keep the process stability at the desired conditions. In this mean, simulation of the treatment system behavior using artificial neural network (ANN) can be an effective tool.  This paper evaluates long term performance and process stability of ...

متن کامل

Performance evaluation of the wastewater treatment plant of Pelareh Dairy Industry, Iran

Pelareh Dairy Industry (PDI) is located in the west of Iran. The aim of the present study was to assess the quality and quantity of PDI wastewater and compare the results with the regulations. PDI has a wastewater treatment plant that consists of sewage collection system, screening system, equalization tank, clarification tank, anaerobic system for pretreatment, activated sludge processing, dis...

متن کامل

Predicting performance of grey and neural network in industrial effluent using 1 online monitoring parameters 2 3 ( Running title :

16 Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids 17 (SSeff), chemical oxygen demand (CODeff) and pHeff in the effluent from conventional activated 18 process of an industrial wastewater treatment plant using simple online monitoring parameters (pH 19 in the equalization pond effluent; pH, temperature, and dissolved oxygen in the aeration tank). Th...

متن کامل

Treatment of small scale gold mining wastewater using pilot-scale sedimentation and Cocopeat filter bed system

The use of amalgamation process to recover gold from mined ores by the small-scale gold miners in the Philippines and other developing countries produces and dispose of untreated wastewater to the receiving water bodies. In this study, a field-scale filter bed system was constructed to treat heavy metal metal-laden wastewater collected from small-scale gold mining site in Paracale, Camarines No...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • JCP

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2012