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基于PCA-GABP神经网络的BOD软测量方法
引用本文:冉维丽,乔俊飞. 基于PCA-GABP神经网络的BOD软测量方法[J]. 控制工程, 2004, 11(3): 212-215
作者姓名:冉维丽  乔俊飞
作者单位:北京工业大学,电子信息与控制工程学院,北京,100022;北京工业大学,电子信息与控制工程学院,北京,100022
基金项目:国家自然科学基金资助项目(50274003和60304012),北京市科技新星计划资助项目(H020821210120)
摘    要:针对污水处理过程中关键水质参数无法在线监测的问题.提出基于PCA-GABP神经网络的污水水质软测量方法。该方法由两部分组成:主元分析PCA和GABP神经网络。其中,GABP算法采用局部改进遗传算法优化神经网络权值。并采用自适应学习速率动量梯度下降算法对神经网络进行训练,建立软测量模型。仿真结果表明该软测量模型稳定性好、精度高,可用于污水处理厂对BOD进行在线预测。

关 键 词:软测量  神经网络  主元分析(PCA)  遗传算法(GA)  污水处理
文章编号:1671-7848(2004)03-0212-04
修稿时间:2003-09-23

Soft-measuring Technique to Predict BOD Based on PCA-GABP Neural Networks
RAN Wei-li,QIAO Jun-fei. Soft-measuring Technique to Predict BOD Based on PCA-GABP Neural Networks[J]. Control Engineering of China, 2004, 11(3): 212-215
Authors:RAN Wei-li  QIAO Jun-fei
Abstract:To the problem that on-line information of some essential wastewater parameters is inaccessible in monitoring and controlling wastewater treatment processes. A soft-measuring technique applied to wastewater quality measurement is put forward based on PCA genetic neural network. It is composed of two elements: principle components analysis (PCA), and genetic neural network. This model can be applied to on-line predict wastewater BOD. Neural network is trained by improved BP algorithm, moreover, applying genetic algorithm to optimize the weights. The simulation results show that the soft-measuring model has good stability and high precision and can be applied to on-line predict wastewater BOD.
Keywords:soft-measuring  neural network  PCA  Genetic Algorithm (GA)  wastewater treatment
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