环境工程学报2013，Vol.7Issue(8)：2997-3000,4.
ABR处理硫酸盐有机废水的BP神经网络建模
Model and simulink of anaerobic baffled reactor treating sulfate organic wastewater based on back-propagation neural network
摘要
Abstract
The back-propagation neural network (BPNN) trained with the data from the sulfate organic wastewater treatment of anaerobic baffled reactor(ABR) and a network model was buih.The better training function and times were ‘ traingda' and 1 900,respectively.Partition connection weights (PCW) was adopted to analyze the dominant factors of effluent COD and SO42-.The results showed that all of the factors (feed COD,SO42-,pH,COD/SO42-and HRT) had an influence on effluent COD and SO42-.Nevertheless,the feed pH was the dominant factor,which relative importance (RI) were 30.79％ and 23.44％,respectively.The model and simulink on restrictive factors for COD and SO42-removal were built respectively,which can be used for prediction on sulfate organic wastewater treatment.关键词
BP神经网络/硫酸盐有机废水处理/厌氧折流板反应器(ABR)/建模/仿真Key words
back propagation neural network/ containing sulfate organic wastewater treatment/ anaerobic baffled reactor (ABR)/ model identification/ simulink分类
资源环境引用本文复制引用
韦添尹,蒋永荣,刘可慧,刘成良,张威..ABR处理硫酸盐有机废水的BP神经网络建模[J].环境工程学报,2013,7(8):2997-3000,4.基金项目
广西自然科学基金资助项目(PF110239,PF120249) （PF110239,PF120249）
广西科学研究与技术开发计划课题(PD12B089) （PD12B089）
广西教育厅项目(LD10071Y,LD12039B(Y)) （LD10071Y,LD12039B(Y）
