%0 Journal Article
%T Classification of water quality based on intelligent total margin adaptive fuzzy support vector machine<br>基于智能全间隔自适应模糊支持向量机的水质分类
%A DAI Hong-liang
%A DAI Dao-qing
%A <br>戴宏亮
%A 戴道清
%J 计算机应用
%D 2008
%I 
%X In this study, Total-margin Adaptive Fuzzy Support Vector Machine (TAFSVM) of good quality was proposed. In addition, Real-valued Genetic Algorithm (RGA) optimized its parameters. Subsequently, the model of Real Genetic Algorithms Total Margin Adaptive Fuzzy Support Vector Machine (RGATAFSVM) was used to classify four kinds of data sets of water quality. The experimental results show that the proposed model can achieve higher classification accuracy and stability than standard support vector machine, BP neural networks and single factor assessment. Consequently, the RGATAFSVM model provides a promising alternative for classification in water quality.
%K Total-margin Adaptive Fuzzy Support Vector Machine (TAFSVM)
%K Real-valued Genetic Algorithms (RGA)
%K water quality
%K classification<br>全间隔自适应模糊支持向量机
%K 实值遗传算法
%K 水质
%K 分类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=B0EE4A0C7042C982C3BB6CAD75910307&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=708DD6B15D2464E8&sid=1EBEF548F614F667&eid=D7BEECB636A8C765&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=17