前置生物膜脱氮污水处理系统的神经网络预测模型研究

针对前置生物膜脱氮污水处理系统（ABAF/0BAF）的多变量、不确定性、非线性等特点,以某污水处理厂的实际运行数据为基础,采用人工神经网络（ANN）的方法,建立了ABAF/0BAF基于混合递阶遗传算法的RBF神经网络预测模型。模型运算结果表明,预测值和实测值能较好地吻合,起到了模拟预测的效果,同时能优化运行状态。该模型的建立为ABAF/0BAF的预测及运行管理供了一条简便实用的途径,具有良好的研究和工程实用价值。

Research of neural network prediction model for pre-denitrification biofilm wastewater treatment system

For the multi-variable,uncertainty,non-linear characteristics of the pre-denitrification biofilm wastewater treatment system（ABAF/0BAF）,a RBF neural network prediction model based on the hybrid hierarchy genetic algorithm is established using the artificial neural network（ANN） approach standing on the actual operation data in the wasterwater treatment system.The results of model calculation show that the predicted value can better match measured value,played a effect of simulating and predicting and be able to optimize the operation status.The establishment of the predicting model provide a simple and practical way for the operation and management in ABAF/0BAF,and have good research and engineering practical value.