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BP神经网络在再生水补给密云水库水质评价中的应用
引用本文:王倩,邹志红.BP神经网络在再生水补给密云水库水质评价中的应用[J].环境科学学报,2014,34(9):2413-2416.
作者姓名:王倩  邹志红
作者单位:2. 华中科技大学环境科学与工程学院, 武汉 430074;2. 华中科技大学环境科学与工程学院, 武汉 430074
基金项目:国家自然科学基金(No.51178018);国家自然科学基金重点资助项目(No.71031001)
摘    要:基于环境质量基本模型,将补给的再生水视为点源污染,建立了再生水补给后的湖库污染物浓度变化模型.在得到补给后主要污染物稳定浓度的基础上,建立BP神经网络模型,使用随机数发生器生成随机数据作为模型的学习样本和检验样本以满足BP模型对样本数量的需求.使用BP模型对再生水补给后的水质进行评价,评价结果证明了再生水补给的可行性与相对安全性.

关 键 词:再生水  零维水质模型  BP模型  水质评价
收稿时间:2013/11/15 0:00:00
修稿时间:2014/1/29 0:00:00

Application of BP neural network in water quality assessment for Miyun Reservoir recharged with reclaimed water
WANG Qian and ZOU Zhihong.Application of BP neural network in water quality assessment for Miyun Reservoir recharged with reclaimed water[J].Acta Scientiae Circumstantiae,2014,34(9):2413-2416.
Authors:WANG Qian and ZOU Zhihong
Affiliation:2. School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074;2. School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074
Abstract:As the reclaimed water was treated as point source pollution, a pollutant concentration model was developed according to the 0-dimensional water quality model. Based on pollutant concentration, BP neural network was used in water quality assessment for Miyun Reservoir recharged with reclaimed water. The study and test samples for the BP neural network were created by randomizer to meet the requirements of the number of samples by a BP model. It is illustrated that it is safe and feasible to use the reclaimed water to supply Miyun Reservoir.
Keywords:reclaimed water  0-dimensional water quality model  bp  water quality assessment
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