Title :
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
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;
Conference_Titel :
Electric Technology and Civil Engineering (ICETCE), 2011 International Conference on
Conference_Location :
Lushan
Print_ISBN :
978-1-4577-0289-1
DOI :
10.1109/ICETCE.2011.5774260
