The fuzzy neural network model of evaluating air environmental quality of city

被引：0

作者：

Xiong, D. G. ^{[1
]}

Li, X. J. ^{[1
]}

Li, J. ^{[1
]}

机构：

[1] Henan Polytechn Univ, Sch Energy Sci & Engn, Jiaozuo City 454003, Henan Province, Peoples R China

来源：

2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 4 | 2008年

关键词：

air quality; comprehensive evaluation; neural network; multi-criteria learning;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper studied a model of evaluating air environmental quality via fuzzy neural network with multi criteria learning algorithm. By regarding the evaluation criteria of air environmental quality as fuzzy sets, using multi-output neural network to acquire an actual output vector and taking it as degree of membership of an evaluated sample to the fuzzy set, the subjective effect on establishing evaluation index of traditional single output network could be overcome. When take the degree of membership vector as weight value and grade the evaluation sample synthetically to evaluate air environmental quality, we can avoid the difficulty in maximum degree of membership criterion when the component of degree of membership vector is not concentrated. The disadvantage of converging slowly and liable to local minimum when adopting single criterion learning neural network could get over by using multi- criterion learning neural network.

引用

页码：637 / 641

页数：5