[1]何争光,孙晓峰,马勇光..AdaBoost-NN模型在浊漳河水质评价中的应用[J].郑州大学学报(工学版),2007,28(01):114-117,121.[doi:10.3969/j.issn.1671-6833.2007.01.029]
　He Zhengguang,SUN Xiaofeng,Ma Yongguang.Application of AdaBoost-NN model in water quality evaluation of Zhuozhang River[J].Journal of Zhengzhou University (Engineering Science),2007,28(01):114-117,121.[doi:10.3969/j.issn.1671-6833.2007.01.029]

点击复制

AdaBoost-NN模型在浊漳河水质评价中的应用()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

28卷

期数:

2007年01期

页码:

114-117,121

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

Application of AdaBoost-NN model in water quality evaluation of Zhuozhang River

作者:

何争光; 孙晓峰; 马勇光.

郑州大学,环境与水利工程学院,河南,郑州,450001, 郑州大学,环境与水利工程学院,河南,郑州,450001, 郑州大学,环境与水利工程学院,河南,郑州,450001

Author(s):

He Zhengguang; SUN Xiaofeng; Ma Yongguang

关键词:

水质评价;  BP网络;  AdaBoost;  泛化

Keywords:

water quality evaluation;  BP Network;  AdaBoost;  Generalization

DOI:

10.3969/j.issn.1671-6833.2007.01.029

文献标志码:

A

摘要:

为了克服传统BP网络的不足,将AdaBoost与神经网络结合,提出了基于AdaBoost-NN的水质评价模型.利用浊漳河水质监测数据比较AdaBoost-NN模型与传统ANN法和内梅罗综合指数法评价模型的差异,结果表明:AdaBoost-NN水质评价模型有效弥补了BP模型自身的缺陷,评价准确度更高,结果更加客观、合理.

Abstract:

In order to overcome the shortcomings of traditional BP networks, a water quality evaluation model based on AdaBoost-NN is proposed by combining AdaBoost with neural networks. The results show that the AdaBoost-NN water quality evaluation model effectively compensates for the shortcomings of the BP model, has higher evaluation accuracy, and the results are more objective and reasonable.

常用功能