Water quality evaluation of nearshore area using artificial neural network model

被引:0
作者
Li Ying [1 ]
Zhou Jiti [1 ]
Wang Xiangrui [2 ]
Zhou Xiaohui [2 ]
机构
[1] Dalian Univ Technol, Sch Environm & Biol Sci & Technol, Dalian, Peoples R China
[2] Dalian Jiatong Univ, Sch Environm & Chem Engn, Dalian, Peoples R China
来源
2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11 | 2009年
关键词
water quality evaluation; Dalian Bay; artificial neural network;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this paper, a water quality evaluation model of nearshore (Dalian Bay) is built through artificial neural network based on the analysis of history information and monitoring data. In which a back propagation (BP) network is used. A hierarchical prediction model is established according to water quality at different period. Results illustrates the methodology is practicable and can be provided scientific proof for water quality evaluation and prevention of Dalian Bay. The method does not demand data's rules and has the characteristic of impersonality, credibility and highly inaccuracy permission. At the same time the predictive relative error is little.
引用
收藏
页码:5962 / +
页数:2
相关论文
共 6 条
[1]   Backfilling missing microbial concentrations in a riverine database using artificial neural networks [J].
Chandramouli, V. ;
Brion, Gail ;
Neelakantan, T. R. ;
Lingireddy, Srinivasa .
WATER RESEARCH, 2007, 41 (01) :217-227
[2]   Neural network modeling of salinity variation in Apalachicola River [J].
Huang, WR ;
Foo, S .
WATER RESEARCH, 2002, 36 (01) :356-362
[3]  
ICAZA Y, 2007, ECOLOGICAL INDICATOR, V7, P710
[4]   A hybrid neural-genetic algorithm for reservoir water quality management [J].
Kuo, JT ;
Wang, YY ;
Lung, WS .
WATER RESEARCH, 2006, 40 (07) :1367-1376
[5]   Evaluation of the ability of an artificial neural network model to assess the variation of groundwater quality in an area of blackfoot disease in Taiwan [J].
Kuo, YM ;
Liu, CW ;
Lin, KH .
WATER RESEARCH, 2004, 38 (01) :148-158
[6]   Use of artificial neural networks to evaluate the effectiveness of riverbank filtration [J].
Sahoo, GB ;
Ray, C ;
Wang, JZ ;
Hubbs, SA ;
Song, R ;
Jasperse, J ;
Seymour, D .
WATER RESEARCH, 2005, 39 (12) :2505-2516