灰色神经网络模型在湖泊水质预测中的应用  

Application of Grey—neural networks Model on Forecastingthe Water Quality

作　　者：陆琦[1] 郭宗楼[1] 姚杰[1] 

机构地区：[1]浙江大学生物系统工程与食品科学学院,浙江杭州310029

出　　处：《农机化研究》2004年第3期159-161,共3页Journal of Agricultural Mechanization Research

基　　金：国家863计划项目(2001AA242121)资助

摘　　要：应用灰色GM(1,1)预测模型和人工神经网络预测模型相结合而成的灰色神经网络模型,对湖泊高锰酸盐指数进行预测。此方法是用人工神经网络去把握灰色GM(1,1)所得到的预测值和实测值之间的未知关系,再进行新的预测。其特点是可行性强,且方法简便。通过准确地预测湖泊高锰酸盐指数可以为治理、控制湖泊营养化和综合利用自然环境资源、规划管理、决策提供重要的科学依据。Grey—neural networks model combined by grey forecasting model and artificial neural networks,we can forecast the lacustrine permanganate value.It is designed to attach importance to the unknown connection between forecasting value and real value which is obtained by GM(1,1) model with artificial neural networks and to forecast again.It is extremely feasible and simple in practice.Forecasting lacustrine permanganate value accurately provides significant scientific basis for harness, controlling the lake eutrophication and making full use of the natural resources, programming, managing and deciding.

关 键 词：灰色神经网络模型 湖泊 水质预测 高锰酸盐指数 

分 类 号：X832[环境科学与工程—环境工程]