The Prediction of River Water Pollution Density Based on Data Mining Technology

摘要：

In order to increase the prediction precision,this article proposes a forecasting model in water pollution density based on data mining technology.The model consists of three stages: first,the rough set theory and the genetic algorithm are applied to select relevant forecasting variable to the water pollution density;second,training pattern of artificial neural network which is similar to the forecast term is carried out by using data mining technology;finally the artificial neural network is used to carry on forecasting the water pollution density.The applied result shows that this model has a higher precision and surpasses gray GM (1,1) and the pure BP artificial neural network model.

关键词： Data Mining Technology BP neural network water pollution density prediction

作者: Chenye Wang Binsheng Liu Erwei Qiu

作者单位: School of Economics & Management,Harbin Engineering University,Harbin 150001,China National Science School of Economics & Management,Harbin Engineering University,Harbin 150001,China National Science Park of Harbin Engineering University,Harbin 150001,China

会议类型: 国际会议

会议名称: 2010 International Conference of Environment Materials and Environment Management(2010年环境材料与环境管理国际学术会议 EMEM 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1285-1288

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）