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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Serapião, A. B. S., & Mendes, J. R. P. (2009). Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5579 LNAI, pp. 301–310). https://doi.org/10.1007/978-3-642-02568-6_31
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