1887

Abstract

Summary

Summary not available

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202084016
2020-09-22
2024-03-28
Loading full text...

Full text loading...

References

  1. [1]Salminen, K., Cheatham, C., Smith, M. et al2017. Stuck-Pipe Prediction by Use of Automated RealTime Modeling and Data Analysis. SPE Drill & Compl32(03): 184–193. SPE-178888-PA. https://doi.org/10.2118/178888-PA
    [Google Scholar]
  2. [2]Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825–2830, 2011
    [Google Scholar]
  3. [3]Christ, M., Kempa-Liehr, A.W. and Feindt, M. (2017). Distributed and parallel time series feature extraction for industrial big data applications. ArXiv e-print 1610.07717, https://arxiv.org/abs/1610.07717.
    [Google Scholar]
  4. [4]Christ, M., Braun, N., Neuffer, J. and Kempa-Liehr, A.W. (2018). Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh -- A Python package). Neurocomputing307 (2018) 72–77, doi:10.1016/j.neucom.2018.03.067.
    https://doi.org/10.1016/j.neucom.2018.03.067 [Google Scholar]
  5. [5]MartínAbadi, AshishAgarwal, PaulBarham, EugeneBrevdo, ZhifengChen, CraigCitro, Greg S.Corrado, AndyDavis, JeffreyDean, MatthieuDevin, SanjayGhemawat, IanGoodfellow, AndrewHarp, GeoffreyIrving, MichaelIsard, RafalJozefowicz, YangqingJia, LukaszKaiser, ManjunathKudlur, JoshLevenberg, DanMané, MikeSchuster, RajatMonga, SherryMoore, DerekMurray, ChrisOlah, JonathonShlens, BenoitSteiner, IlyaSutskever, KunalTalwar, PaulTucker, VincentVanhoucke, VijayVasudevan, FernandaViégas, OriolVinyals, PeteWarden, MartinWattenberg, MartinWicke, YuanYu, and XiaoqiangZheng. TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. Software available from tensorflow.org.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202084016
Loading
/content/papers/10.3997/2214-4609.202084016
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error