[1]王亦斌,孙 涛,陈 谌.随机森林与模糊识别耦合方法在河流健康评价中的应用[J].江苏水利,2019,(05):25-29.
　WANG Yibin,SUN Tao,CHEN Chen.Application of random forest and fuzzy recognition coupling method in river health assessment[J].JIANGSU WATER RESOURCES,2019,(05):25-29.
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随机森林与模糊识别耦合方法在河流健康评价中的应用()
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《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2019年05期
页码:
25-29
栏目:
水生态与环境
出版日期:
2019-05-23

文章信息/Info

Title:
Application of random forest and fuzzy recognition coupling method in river health assessment
文章编号:
1007-7839(2019)05-0025-05
作者:
王亦斌1;  孙 涛1;  陈 谌2
1.南水北调东线江苏水源有限责任公司, 江苏 南京 210029; 2.南京工业大学 电气工程与控制科学学院, 江苏 南京 211816
Author(s):
WANG Yibin1;  SUN Tao1;  CHEN Chen2
1.Jiangsu water source limited liability Company of South to North Water Transfer East line,Nanjing 210029, Jiangsu; 2.College of Electrical Engineering and Control Science,Nanjing Tech University, Nanjing 211816, Jiangsu
关键词:
河流健康评价;  相对隶属度;  随机森林;  模糊识别
Keywords:
river health assessment;  relative membership degree;  random forest;  fuzzy identification
分类号:
X826
文献标志码:
B
摘要:
随着现代社会对生态环境关注度的提高,而河流在生态环境中又起到了举足轻重的作用,如何准确构建河流健康评价模型成为了河流治理的关键内容。研究首先建立河流健康评价指标体系,利用随机森林gini指数计算出每个指标的权重,再构建指标相对隶属度函数,最后进行模糊识别综合计算,并将其应用到某市6条主要河流的健康评价中。试验结果表明:编号为1～5的河流评价结果均在[0.70,0.85]之间,评价等级为良; 编号为6的河流评价结果在0.70以下,评价等级为差,说明本文方法的评价结果与实际河流评价情况基本一致。因此,本文提出的随机森林与模糊识别耦合方法合理、可行,不仅科学合理地确定了河流健康评价指标的权重,也提高了模型评价的准确性。
Abstract:
With the increasing attention paid to the ecological environment in modern society, rivers play a decisive role in the ecological environment.How to accurately build river health evaluation model has become the key content of river governance.Firstly, the river health evaluation index system was established, the weight of each index by using gini index of stochastic forest was calculated.Then, the relative membership function of the index was constructed.Finally, the comprehensive calculation of fuzzy recognition was carried out and applies to the health evaluation of six main rivers in a city.The test results showed that the evaluation results of rivers numbered 1-5 were between [0.70, 0.85], and the evaluation grade was good; the evaluation results of rivers numbered 6 were below 0.70, and the evaluation grade was poor, which showed that the evaluation results of this method were basically consistent with the actual river evaluation situation.Therefore, the coupling method of random forest and fuzzy identification proposed was reasonable and feasible.It not only determined the weight of river health evaluation index scientifically and reasonably, but also improved the accuracy of model evaluation.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-10-4
基金项目:国家自然科学基金青年基金项目(11801267); 国家重点研发计划项目(2017YFC1502603)
作者简介:王亦斌(1970—),女,本科,高级工程师,主要从事水利工程建设与管理工作。
通讯作者:陈谌(1993—),男,硕士,研究方向为智能算法、模式识别。
更新日期/Last Update: 2019-05-15