Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River

GUO Qing-chun; HE Zhen-fang; LI Li; Kou Li-qun

您当前的位置：

首页 >

文章列表页 >

Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River

- Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River
- Bulletin of Soiland Water Conservation Vol. 30, Issue 4, Pages: 112-115(2011)
- 作者机构：
  
  1. 陕西广播电视大学教务处,陕西,西安,710068
  2. 中国科学院寒区旱区环境与工程研究所,陕西,西安,710075
  3. 中国科学院地球环境研究所,甘肃,兰州,730000
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2011
- 稿件说明：
移动端阅览
GUO Qing-chun, HE Zhen-fang, LI Li, et al. Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River[J]. Bulletin of Soiland Water Conservation, 2011, 30(4): 112-115.
DOI：

GUO Qing-chun, HE Zhen-fang, LI Li, et al. Application of BP Neural Network on Water Environmental Quality Evaluation of Weihe River[J]. Bulletin of Soiland Water Conservation, 2011, 30(4): 112-115. DOI：

摘要

为准确和客观地评价渭河水环境质量状况，将改进算法的BP神经网络引入地表水环境质量评价领域，采用渭河2010年(9月7日至10月11日)水质指标监测数据，构建了渭河水环境质量评价模型。通过3个水质监测项目(氨氮、高锰酸盐指数、溶解氧)对渭河水质进行了评价，评价结果与环境保护部公布结果完全一致。结果表明，BP神经网络应用于水环境质量评价具有客观性、通用性和实用性，可以很好地解决评价因子与水质等级间复杂的非线性关系，评价方法简便可靠，预测精度高。

Abstract

In order to evaluate the surface water environment quality accurately and objectively

the BP neural network with improved algorithms is introduced in water environmental quality evaluation.Water environment quality evaluation model of the Weihe River was constructed with recorded data of water quality during the period from Sep.7 to Oct.11 in 2010.Water quality of the Weihe River was evaluated through 3 water quality monitoring projects(NH3N

potassium permanganate index

DO)

and the evaluation results by the BP neural network and by the environmental protection department were compared

and both evaluation results are identical.The results showed that the BP neural network model could well solve complex nonlinear relation between the evaluation factors and water quality levels

and the method was simple and reliable

and the forecast precision was high.The BP neural net work for water environmental quality evaluation is objective

universal and practical.

关键词

Keywords

references

Views

1926

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Intelligent Evaluation of Loess Collapsibility

Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation

Distribution of Heavy Metal Speciation in Surface Sediment of Weihe River at Xianyang Section

A Constitutive Model of Grassroots-reinforced Soil Based on BP Neural Network

Characteristics of Non-Point Source Pollution and Load of Weihe River Based on Storm Runoff Monitoring Data

Related Author

LI Yingliang

SONG Xueqing

CUI Zhongxing

WU Yanqing

JING Yanlin

SHEN Bing

SONG Xiao-yu

ZHOU Jian-guo

Related Institution

Electronic Comprehensive Investigation and Surveying Institute of Ministry of Information Industry

Xi’an Design and Research Institute of Coal Industry

Xi’an University of Technology

Institute of Water Resources, Xi’an University of Technology

⁰