人民黄河Issue(5)：67-70,110,5.DOI:10.3969/j.issn.1000-1379.2014.05.021
基于人工神经网络的泾河陕西段氮组分模拟
Simulation and Prediction of Water Quality Nitrogen based on ANN in Jinghe River, Shaanxi Province
摘要
Abstract
River water quality simulation provides theory evidence for pollutants variation in water environment. By using BP algorithm of ANN,the paper simulated the concentration of ammonia nitrogen,nitrate nitrogen and total nitrogen in Jinghe River,Shaanxi Province. The input parameters of BP network model were selected through simultaneous analysis on correlation between the output parameters and water quality parameters and mechanism modeling of river water quality. The BP network models with different structures were built based on the input and output parameters which were mainly decided by the studied problems. The models were trained and validated using monthly observed data of hydrology,water quality and precipitation. The results show that the BP models of nitrate nitrogen and total nitrogen can precisely simulate the variation of water quality and the errors of water quality simulation with different structures are less than 18%;the models of ammonia nitrogen produce big errors which are prob-ably related to the source of ammonia nitrogen. Ammonia nitrogen comes from the point source discharge and has instability discharge all over three years to cause the big simulation errors. At the same time the simulation results show that the precisions of the models simulating one water quality parameter exceed the ones simulating three parameters;the BP models with one hidden layer exceed the ones with two and three hidden layers in precision.关键词
水质模拟/人工神经网络/BP算法/氮/泾河Key words
water quality simulation/ANN/BP algorithm/Nitrogen/Jinghe River分类
资源环境引用本文复制引用
王菊翠,陈书中,仵彦卿,胡安焱..基于人工神经网络的泾河陕西段氮组分模拟[J].人民黄河,2014,(5):67-70,110,5.基金项目
国家自然科学基金资助项目（10572090）；陕西省自然科学基金资助项目（2006D16）。 （）
