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.
出处
《环境污染与防治》
CAS
CSCD
北大核心
2004年第5期351-354,共4页
Environmental Pollution & Control
