[1]朱永军,吴 琼,湛忠宇.基于主成分分析法与人工神经网络耦合模型的水质评价[J].江苏水利,2021,(08):48-54.
　ZHU Yongjun,WU Qiong,ZHAN Zhongyu.Study on water quality evaluation of Luhe District based on principal component analysis and artificial neural network coupling model[J].JIANGSU WATER RESOURCES,2021,(08):48-54.
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基于主成分分析法与人工神经网络耦合模型的水质评价()
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《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2021年08期
页码:
48-54
栏目:
水生态与环境
出版日期:
2021-08-31

文章信息/Info

Title:
Study on water quality evaluation of Luhe District based on principal component analysis and artificial neural network coupling model
文章编号:
1007-7839(2021)08-0048-07
作者:
朱永军; 吴 琼; 湛忠宇
(江苏省水文水资源勘测局南京分局,江苏 南京 210008)
Author(s):
ZHU Yongjun; WU Qiong; ZHAN Zhongyu
(Nanjing Hydrology and Water Resources Survey Bureau of Jiangsu Province,Nanjing 210008,China)
关键词:
主成分分析;  人工神经网络;  水质评价;  水环境改善;  六合区
Keywords:
principal component analysis;  artificial neural network;  water quality evaluation;  water environment improvement;  Luhe District
分类号:
TV21
文献标志码:
B
摘要:
为了解决水质评价中评价指标权重难以合理确定、评价模型过于复杂、评价结果不合理等问题,将改进的主成分分析降维能力与人工神经网络自学习能力相结合,提出PCA-BP神经网络水质评价模型。实例分析表明,PCA-BP神经网络在避免了传统的单因子评价法评价结果过于悲观、神经网络法模型复杂的同时,能够确定主要污染物,所得评价结果的合理性、准确性均能够得到保证。
Abstract:
In order to solve the problems in water quality evaluation,such as difficulty in determining the weight of evaluation indexes,too complicated evaluation model and unreasonable evaluation results,the improved dimension-reduction ability of principal component analysis was combined with the self-learning ability of artificial neural network,and the PCA-BP neural network model for water quality evaluation was proposed. The case analysis showed that PCA-BP neural network could avoid the pessimistic evaluation result of the traditional single factor evaluation method,and the model of the neural network method was complex. At the same time,it could determine the main pollutants,and the rationality and accuracy of the evaluation results could be guaranteed.

参考文献/References:

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相似文献/References:

[1]周必翠,吕照根,舒持恺,等.基于主成分分析的河流健康指标权重分配研究[J].江苏水利,2017,(06):16.
　ZHOU Bicui,LV Zhaogen,SHU Chikai,et al.Study on the weight distribution of river health index based on principal component analysis[J].JIANGSU WATER RESOURCES,2017,(08):16.
[2]石 全,张建华,王会容,等.河网区水污染控制影响因素诊断分析[J].江苏水利,2018,(04):22.
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备注/Memo

备注/Memo:
收稿日期:2020-12-31
作者简介:朱永军(1970—),男,工程师,研究方向为水资源与水环境管理。E-mail:1139094860@qq.com
更新日期/Last Update: 2021-08-31