Research on prediction of water quality of water reservoir with combined Multiple Neural Networks model

Author

Lin, Wang ; Ran, Li ; Youcai, Tuo ; Kefeng, Li

Author_Institution

State Key Lab. of Hydraulics & Mountain River Eng., Sichuan Univ., Chengdu, China

fYear

2011

fDate

22-24 April 2011

Firstpage

4376

Lastpage

4379

Abstract

Previously, it is not easy to solve problems like having a lot of Water Factors, being hard to express the whole process of change when use deterministic model to predict the water quality. In order to solve the problem, the essay founded and used BP and RBF, the predict model of combined Multiple Neural Networks to check and simulate the data of water quality monitoring of Fengman Reservoir on the Songhua River from 1985 to 2010. The result is that the prediction is obviously better than using previous Single Neural Network. The prediction is more accurate and practical. It can provide better support of decision on management of water environment of the reservoir.

Keywords

backpropagation; quality management; radial basis function networks; reservoirs; rivers; BP; Fengman reservoir; RBF; Songhua river; multiple neural network model; water quality monitoring; water quality prediction; water reservoir; Artificial neural networks; Biological system modeling; Computer languages; Predictive models; Reservoirs; Rivers; BP neural network; RBF neural network; combined model; water quality prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Technology and Civil Engineering (ICETCE), 2011 International Conference on

Conference_Location

Lushan

Print_ISBN

978-1-4577-0289-1

Type

conf

DOI

10.1109/ICETCE.2011.5774260

Filename

5774260