Qiumei Cong

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Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model:(More)
Poor-quality data has become a serous problem to the model, control and optimization. An improved robust EMPCA integrated with fuzzy c-means (FCM) clustering is used to classify the operational state in the activated sludge process. The method is demonstrated by IWA simulation benchmark. The experimental results show the proposed the method can accurately(More)
Due to high complex of the biological wastewater treatment, it is difficult to develop an accurate mathematics model. A hybrid dynamic modeling in both parallel and serial configuration was used in an anoxic-aeration activated sludge process. In the hybrid model, case-based reasoning (CBR) system is placed in series with a mechanistic model, which was the(More)
The measurements of many key parameters and effluent qualities in WWTP (wastewater treatment plant) are impossible due to the lack of precise online sensors and strong time-delay of WWTP process. The fuzzy neural network (FNN) based effluent COD (chemical oxygen demand) of activated sludge SBR (sequential batch reactor) prediction model is built in this(More)
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