Title :
Water quality assessment based on BP network and its application
Author :
Hao Zhu-lin ; Zhang Yuan-yuan ; Feng Min-quan
Author_Institution :
Key Lab. of Northwest Water Resources & Environ. Ecology of Educ. Minist., Xi´an Univ. of Technol., Xi´an, China
Abstract :
The multilayer feed forward neural network (BP network) method was applied to evaluate water quality in order to determine the water quality in Fen river of Yuncheng section. Surface water limits of worse than V water was defined. Training sample was generated based on classification standard, then the water quality was evaluated by BP network that could be trained in Fen river of Yuncheng section. The water is polluted seriously in Fen river of Yuncheng section, The water quality is the standard of Worse than grade V in Xinjiang Zhanli monitoring section and Hejin Bridge monitoring section during 2005-2009. There is no time to delay the Implementation of pollution gross control. The BP network model can make full use of the water quality data to establish the complex nonlinear relationship between input and output. Large number of parameters in the network are obtained by learning, not given by man-made so that influence of human factors are avoided. The evaluation results are more objective and reasonable.
Keywords :
backpropagation; environmental science computing; multilayer perceptrons; rivers; water quality; water resources; Fen river; Yuncheng section; backpropagation network; multilayer feedforward neural network; water pollution; water quality assessment; Artificial neural networks; Indexes; Monitoring; Quality assessment; Rivers; Water pollution; Water resources; BP network; Fen River; the comprehensive water quality identification index; water quality assessment;
Conference_Titel :
Water Resource and Environmental Protection (ISWREP), 2011 International Symposium on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-339-1
DOI :
10.1109/ISWREP.2011.5893150
