[1]关成立[][],杨岳[],陈兴汉[][]. 基于BP神经网络的线路板废水处理研究[J].计算机技术与发展,2015,25(08):194-198.
 GUAN Cheng-li[] [],YANG Yue[] CHEN Xing-han[][]. Research on Wastewater Treatment Process of Printed Circuit Board Based on Neural Network[J].,2015,25(08):194-198.
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 基于BP神经网络的线路板废水处理研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年08期
页码:
194-198
栏目:
应用开发研究
出版日期:
2015-08-10

文章信息/Info

Title:
 Research on Wastewater Treatment Process of Printed Circuit Board Based on Neural Network
文章编号:
1673-629X(2015)08-0194-05
作者:
 关成立[1][2] 杨岳[1] 陈兴汉[1][3]
1. 阳江职业技术学院 网络信息中心;2. 广东技术师范学院 计算机科学学院;3. 中山大学 生命科学学院
Author(s):
 GUAN Cheng-li[1] [2]YANG Yue[1] CHEN Xing-han[1][3]
关键词:
 BP神经网络线路板废水化学试剂处理训练预测
Keywords:
 BP neural networkPCB wastewaterchemical reagenttreatmenttrainingprediction
分类号:
TP39
文献标志码:
A
摘要:
 为了缩短印制线路板产业( PCB)废水处理的调试周期,控制化学试剂用量,节约能源,采用反向传播( BP)神经网络训练并建立了线路板废水处理的神经网络模型。以混凝沉淀水处理工艺的5个主要影响因素作为输入层参数,以出水水质指标作为输出层参数,设置单隐含层。将10组调试数据作为训练样本,网络运行得到的系统误差为0.00099996,将3组调试数据作为预测样本,网络预测值与实际数据值吻合较好。说明该网络具有较好的泛化能力,能很好地对在不同水质参数下线路板废水的处理效果进行预测,在达到所要求的水处理效果的基础上,降低进水水量及水质变化系数较大等不利因素的影响,合理投加化学试剂,使水处理系统在最优的状态下安全、稳定、低成本及高效率运行。
Abstract:
 In order to shorten the debugging cycle of wastewater treatment in Printed Circuit Board ( PCB) production,control the chemi-cal reagent consumption and save energy sources,Back Propagation ( BP) neural network is trained and built for PCB wastewater treat-ment. The five key influential factors on coagulation water treatment technology are regarded as characteristic input vectors,and the efflu-ent quality index as output vectors. The debug data are divided into train group and prediction group. Running the BP neural network,the system error is 0. 000 999 96 and the network prediction is in good agreement with the actual data values,showing the precision and the generalization of network is good. Based on the wastewater treatment efficiency,the BP neural network provides a window to reduce the effect of unfavorable factors such as the influent water quantity and quality,adding the chemical reagent reasonably,ensuring the smooth operation of the system,minimizing the operation costs and improving the treatment efficiency.

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更新日期/Last Update: 2015-09-14