Carrousel氧化沟系统出水COD预报的神经网络模型  

The ANN Model Predicting Effluent COD of Carrousel Oxidation Ditch System

作　　者：罗亚田[1] 廖润华[2] 陈安[1] 孙耀华[3] 王勉[3] 

机构地区：[1]武汉理工大学资源与环境工程学院,湖北武汉430070 [2]景德镇陶瓷学院材料科学与工程学院,江西景德镇333001 [3]河南省漯河市污水净化中心,河南漯河462000

出　　处：《环境污染与防治》2004年第5期351-354,共4页Environmental Pollution & Control

摘　　要：以河南漯河市污水净化中心的氧化沟系统为考察对象 ,针对该系统进水水质复杂 ,控制滞后的难点 ,引入人工神经网络的理论和方法 ,对其进行模拟分析 ,建立了基于 BP网络的氧化沟系统出水 COD预报模型。模型性能检验和灵敏度检验表明 ,建成的模型准确度高 ,适应性强 ,可直接用于该系统出水 COD预报。The carrousel oxidation ditch system in Wastewater Treatment center of Luohe is difficult to be controlled on-line because the influent characteristics are complex and various significantly. To resolve the problem, advanced artificial neural network (ANN) was employed to simulate the correlation between water parameters of oxidation ditch system and a BPNN model predicting effluent COD was built up. Sentivity and performance tests showed that the model can adapt to different situations and has good ability to generalize. It can be directly used to predict effluent COD concentration, which is very helpful to oxidation ditch system control on-line.

关 键 词：COD CARROUSEL氧化沟 出水 氧化沟工艺 污水净化 水质 神经网络模型 系统 漯河市 河南 

分 类 号：X703[环境科学与工程—环境工程] X505