College of Electrical Engineering, Hebei United University, Hebei Tangshan 063009, China

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Abstract—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.

Index Terms—NW small-world networks, multi-layer forward neural networks, wastewater plant, modeling, wastewater treatment.

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Cite: Ruicheng Zhang, Xulei Hu, "Effluent Quality Prediction of Wastewater Treatment System Based on Small-world ANN," Journal of Computers vol. 7, no. 9, pp. 2136-2143, 2012.