Applying genetic algorithm for training hybrid neuro-fuzzy classifier -: the nfgClass system

被引：0
|
作者：
Gradzki, P [1 ]
机构：
[1] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland
来源：
NEURAL NETWORKS AND SOFT COMPUTING | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper briefly presents the nfgClass system - the hybrid neuro-fuzzy(genetic) classifier that can be applied for designing intelligent decision support systems. The learning abilities of the presented system can be substantially improved by applying a genetic algorithm as. In order to compare the performance of the systems trained with different learning algorithms, there were built two decision support systems for the glass identification problem and another two for the abalone species age problem. In both cases the first system was trained with conjugate gradient algorithm and the second one with the genetic algorithm.
引用
收藏
页码：510 / 515
页数：6
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