Parallel fuzzy learning

被引：0
|
作者：
Russo, M
机构：
[1] Univ Messina, Dept Phys, I-98166 Messina, Italy
[2] Ist Nazl Fis Nucl, Natl Inst Phys, Sect Catania, I-95129 Catania, Italy
来源：
FOUNDATIONS AND TOOLS FOR NEURAL MODELING, PROCEEDINGS, VOL I | 1999年 / 1606卷
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：
GEFREX is a genetic-neuro-fuzzy tool able to extract very compact fuzzy rules. It is mainly based on the genetic paradigm. This paper shows the preliminary result obtained by the author regarding the parallelization of this tool. The hw platform consists of a cluster of 7 PC-based single pentium II 233 MHz workstations and 1 PC-based double pentium II 300 MHz processor server. The communication network is a fast-ethernet dedicated LAN. The results achieved are very promising. With up to seven processing elements, the speedup obtainable is linear.
引用
收藏
页码：641 / 650
页数：10
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