A Statistical Feature-Based Approach for Operations Recognition in Drilling Time Series

Research output: Contribution to journalArticleResearchpeer-review

Standard

A Statistical Feature-Based Approach for Operations Recognition in Drilling Time Series. / Esmael, Bilal; Arnaout, Arghad; Fruhwirth, Rudolf et al.
In: International Journal of Computer Information Systems and Industrial Management Applications , Vol. 4, No. 6, 2012, p. 100-108.

Research output: Contribution to journalArticleResearchpeer-review

Bibtex - Download

@article{4459a5d0a7974b23a394a9381ec8c3c5,
title = "A Statistical Feature-Based Approach for Operations Recognition in Drilling Time Series",
author = "Bilal Esmael and Arghad Arnaout and Rudolf Fruhwirth and Gerhard Thonhauser",
year = "2012",
language = "English",
volume = "4",
pages = "100--108",
journal = "International Journal of Computer Information Systems and Industrial Management Applications ",
issn = "2150-7988",
publisher = "Machine Intelligence Research Labs",
number = "6",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - A Statistical Feature-Based Approach for Operations Recognition in Drilling Time Series

AU - Esmael, Bilal

AU - Arnaout, Arghad

AU - Fruhwirth, Rudolf

AU - Thonhauser, Gerhard

PY - 2012

Y1 - 2012

M3 - Article

VL - 4

SP - 100

EP - 108

JO - International Journal of Computer Information Systems and Industrial Management Applications

JF - International Journal of Computer Information Systems and Industrial Management Applications

SN - 2150-7988

IS - 6

ER -