Nonlinear Forecast System for River Water Pollution Based on GIS
TAN Qin - wen, YIN Guang - zhi, LI Dong - wei
DOI:10.11835/j.issn.1674-4764.2006.05.027
Received March 20, 2006,Revised March 20, 2006, Accepted , Available online July 01, 2015
Volume ,2006,Pages 115-118
- Abstract
Based on the analysis of the water pollution spatial distribution characters of Yangtze River in Chongqing,a new method based on the integration of BP neural network and genetic arithmetic(GA) is proposed.For some shortcomings existed in the standard BP neural network,this method has ultimately overcome these shortcomings by combining the GA with BP artificial neural network through altering stimulating function,adding momentum factor to power value for BP algorithm and introducing genetic arithmetic to searching for the knots of the hidden layer,momentum factor and learning level.Using this method can easily overcome the difficulty of measuring the water prediction model's parameters.GIS is used as a tool for data management and spatial analysis,and the prediction result of the model for the water pollution spatial distribution characters of Yangtze River in Chongqing is visualized and explored with the precision of more than 78%.