采用LS-SVM的自来水厂沉淀池出水浊度建模  被引量:1

Forecast Model for Settling Tank Water Turbidity in Waterworks Using LS-SVM

在线阅读下载全文

作  者:贾金明[1,2] 陈学剑 

机构地区:[1]东南大学经济管理学院,江苏南京210096 [2]连云港市自来水有限责任公司,江苏连云港222001

出  处:《自动化仪表》2009年第3期63-65,共3页Process Automation Instrumentation

摘  要:加药混凝过程是自来水厂生产工艺的一个重要环节,如何对沉淀池出水浊度进行预测一直是个热点问题。自来水厂加药混凝过程是大滞后、非线性和时变的复杂动态系统,针对这一过程进行机理模型分析非常困难的特点,采用最小二乘支持向量机(LS-SVM)对这一过程进行建模研究,给出了沉淀池出水浊度预测模型。通过实际应用表明建立的预测模型拟合误差小、推广性能好,具有较好的预测效果,可以应用到对加药混凝过程进行优化和控制中。Chemical dosage and flocculation are important procedures in production of waterworks ; and prediction of outlet water from precipitating tank is always the key point. It is very difficult to do the analysis on mechanism model for the dosing and flocculation process because the process is a complicated dynamic system which features large time lag, nonlinear, and time varying. By using least square support vector machine ( LS-SVM ), the modeling research is conducted for the process ; and the predictive model of turbidity of outlet water is established. The practical application shows that the model offers small fitting error,good to be propagated ,and better predicted effects. It can be used on optimization and control of the dosing and floceulation process.

关 键 词:最小二乘支持向量机 加药 混凝 预测 浊度 模型 

分 类 号:TU991.21[建筑科学—市政工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象