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Proceedings Paper

Prediction of wastewater treatment plants performance based on artificial fish school neural network
Author(s): Ruicheng Zhang; Chong Li
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Paper Abstract

A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on 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.

Paper Details

Date Published: 29 October 2011
PDF: 6 pages
Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 82050T (29 October 2011); doi: 10.1117/12.906345
Show Author Affiliations
Ruicheng Zhang, Hebei Polytechnic Univ. (China)
Chong Li, Hebei Polytechnic Univ. (China)


Published in SPIE Proceedings Vol. 8205:
2011 International Conference on Photonics, 3D-Imaging, and Visualization
Egui Zhu, Editor(s)

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