摘要
金属矿山尾矿库废水中含有H+ 、CN-和多种金属离子 ,是矿区及其流域酸性污染和金属污染的主要污染源。在收集某铜铁矿尾矿库废水 1 4年水质监测资料基础上 ,运用人工神经网络的改进BP算法对其 8项水质指标进行了分析、分类和仿真预测 ,揭示了该矿尾矿库废水的污染特性 。
The wastewater of the tailings reservior of metal mine,which contains H +,CN - and many kinds of metal ions,is the major acid and metal pollution sourc in the mining district and its drainage area.Based on the collected 14 years' water quality information data of the wastewater of a copper-iron mine's tailings reservoir,the improved BP algorithm of artificial neural network is used to analyse,classify and predict by simulation of eight indexes of water quality exposing the pollution characteristics of the wasterwater of this mine's tailings and identifying the main polltants.
出处
《金属矿山》
CAS
北大核心
2003年第11期49-51,63,共4页
Metal Mine
基金
国家自然科学基金资助项目 ( 5 0 2 64 0 0 3 )
江西省教育厅资助项目
关键词
人工神经网络
尾矿库废水
水质预测
网络预测
铜铁矿
Artificial neural network,Wastewater of tailings reservoir,Prediction of water quality
