Classification of Petroleum Well Drilling Operations with a Hybrid Particle Swarm/Ant Colony Algorithm

被引：0
|
作者：
Serapiao, Adriane B. S. [1 ]
Mendes, Jose Ricardo P. [2 ]
机构：
[1] UNESP, IGCE, DEMAC, CP 178, BR-13506900 Rio Claro, SP, Brazil
[2] Univ Estadual Campinas, FEM, DEP, Campinas, SP, Brazil
来源：
NEXT-GENERATION APPLIED INTELLIGENCE, PROCEEDINGS | 2009年 / 5579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：
This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining.
引用
收藏
页码：301 / +
页数：2
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