Development of a full-scale artificial neural network model for the removal of natural organic matter by enhanced coagulation

被引：51

作者：

Baxter, CW ^{[1
]}

Stanley, SJ ^{[1
]}

Zhang, Q ^{[1
]}

机构：

[1] Univ Alberta, Dept Civil & Environm Engn, Environm Sci & Engn Program, Edmonton, AB T6G 2M8, Canada

来源：

JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA | 1999年 / 48卷 / 04期

关键词：

D O I：

10.2166/aqua.1999.0013

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Described is the development of a full-scale artificial neural network (ANN) model for the removal of natural organic matter (NOM) by enhanced coagulation at the Rossdale Water Treatment Plant (WTP) in Edmonton, Alberta, Canada. Few attempts have been made to develop a full-scale model of the enhanced coagulation process due to extreme variability in the process parameters and the complex nonlinear relationships between them. When applied to previously unseen data, the model predicted effluent colour with a high degree of accuracy. The model will be incorporated into real-time process control at the WTP following a period of online testing.

引用

页码：129 / 136

页数：8