Optimising a neural tree classifier using a genetic algorithm

被引：0
|
作者：
Pensuwon, W [1 ]
Adams, R [1 ]
Davey, N [1 ]
机构：
[1] Univ Hertfordshire, Dept Comp Sci, Hatfield AL10 9AB, Herts, England
来源：
KES'2000: FOURTH INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ENGINEERING SYSTEMS & ALLIED TECHNOLOGIES, VOLS 1 AND 2, PROCEEDINGS | 2000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：
This paper documents experiments performed using a GA to optimise the parameters of a dynamic neural tree model. Two fitness functions were created from two selected clustering measures, and a population of genotypes, specifying parameters of the model were evolved. This process mirrors genomic evolution and ontogeny. It is shown that the evolved parameter values improved performance.
引用
收藏
页码：848 / 851
页数：4
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