Intelligent Modeling Approach to Predict Effluent Quality of Wastewater Treatment Process

Hong-gui Han, Xiaolong Wu, Lu Zhang, J. Qiao
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引用次数: 2

Abstract

Monitoring of effluent quality remains a challenge to the wastewater treatment process (WWTP). In order to provide a reliable tool for the online monitoring of effluent quality, an intelligent modeling approach, which consists of online sensors and an effluent quality predicting plant, is developed to predict effluent quality in this chapter. The intelligent modeling approach, based on a self-organizing fuzzy neural network (SOFNN), is able to enhance the modeling performance by organizing the structure and adjusting the parameters simultaneously. The experimental studies of intelligent modeling approach have been performed on several systems to verify the effectiveness. The comparison with other existing methods has been made and demonstrated that the intelligent modeling approach is of better performance.
污水处理过程出水水质预测的智能建模方法
对污水处理过程(WWTP)的出水质量监测仍然是一个挑战。为了给出水水质的在线监测提供可靠的工具,本章提出了一种由在线传感器和出水水质预测装置组成的出水水质智能建模方法。基于自组织模糊神经网络(SOFNN)的智能建模方法通过同时组织结构和调整参数来提高建模性能。在多个系统上进行了智能建模方法的实验研究,验证了该方法的有效性。并与现有的智能建模方法进行了比较,结果表明该方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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