[1]张天琪.基于BP神经网络算法的河湖生态健康评价研究[J].江苏水利,2020,(06):15-19.
　ZHANG Tianqi.Study on the ecological health evaluation of rivers and lakes based on BP neural network algorithm[J].JIANGSU WATER RESOURCES,2020,(06):15-19.
点击复制

基于BP神经网络算法的河湖生态健康评价研究()
分享到：

《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年06期
页码:
15-19
栏目:
水生态与环境
出版日期:
2020-07-01

文章信息/Info

Title:
Study on the ecological health evaluation of rivers and lakes based on BP neural network algorithm
文章编号:
1007-7839(2020)06-0015-05
作者:
张天琪
江苏省泰州引江河管理处, 江苏 泰州 225300
Author(s):
ZHANG Tianqi
Jiangsu Taizhou Leading River Administrative Office, Taizhou 225300, China
关键词:
BP神经网络;  河湖生态;  健康指数;  评价指标
Keywords:
BP neural network;  river and lake ecology;  health index;  evaluation indicator
分类号:
X826
文献标志码:
B
摘要:
研究提出利用BP神经网络智能算法对河湖生态健康进行评价,通过构建基于BP神经网络的河湖生态健康评价系统模型,根据评价指标的数量设定BP神经网络输入层节点个数为18,同时依据河湖生态健康指数的种类个数设定输出层节点为5个。通过训练BP神经网络模型,在第573次迭代的时候,训练模型满足所设定的误差要求,所得到的BP神经网络模型可根据相关评价指标准确评价河湖生态健康指数。
Abstract:
BP neural network intelligent algorithm was proposed to evaluate the ecological health of rivers and lakes. By constructing a model of river and lake ecological health evaluation system based on BP neural network, the number of BP neural network input layer nodes were set to 18 according to the number of evaluation indicators, while the output layer nodes were set to 5 according to the species number of the ecological health index of rivers and lakes. By training the BP neural network model, the training model met the set error requirements at the 573th iteration. The obtained BP neural network model could accurately evaluate the ecological health index of rivers and lakes according to relevant evaluation indicators.

参考文献/References:

[1] 崔东文, 金波. 基于随机森林回归算法的水生态文明综合评价[J]. 水利水电科技进展, 2014, 35(5):56-60.
[2] 王桂林, 郦息明, 陶淑芸. 连云港市典型河湖健康评价研究[J]. 江苏水利, 2017(3):28-33.
[3] 张智伟. 江苏省河流健康评价指标体系细化研究[J]. 江苏水利, 2016(7):27-29.
[4] 段长桂, 董增川, 管西柯, 等. 基于猴群算法的投影寻踪模型在河流健康评价中的应用[J]. 水电能源科学, 2017(10):57-60.
[5] 单红喜. 基于模糊数学的河道健康综合评价方法研究[J]. 江苏水利, 2018(5):61-66.
[6] 刘飞, 凌洪军, 路广宽. 基于改进随机森林算法的通榆河水生态健康状况评价研究[J]. 江苏水利, 2019(10):18-22.
[7] XU M, ZENG G M, XU X Y. Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data:a case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake[J]. Journal of Environmental Sciences, 2005, 17(6):946-952.
[8] MO M, WANG X, WU H, et al. Ecosystem health assessment of Honghu Lake Wetland of China using artificial neural network approach[J]. Chinese Geographical Science, 2009(4):61-68.

相似文献/References:

[1]贡瑞金.苏州系统治水的实践与启示[J].江苏水利,2019,(增刊2):1.
　GONG Ruijin.Practice and enlightenment of systematic water control in Suzhou[J].JIANGSU WATER RESOURCES,2019,(06):1.

备注/Memo

备注/Memo:
收稿日期:2020-02-20
作者简介:张天琪(1995—),女,本科,研究方向为微机继电保护及河道治理评价。E-mail:tianqi_zhang1995@163.com
更新日期/Last Update: 2020-06-20