piwik-script

Deutsch Intern
Chair of Computer Science II - Software Engineering

Publications

Journal and Magazine Articles

  • A Machine Learning-based Workflow for Automatic Detection of Anomalies in Machine Tools. Züfle, Marwin; Moog, Felix; Lesch, Veronika; Krupitzer, Christian; Kounev, Samuel; in ISA Transactions: The Journal of Automation (2021).
    (in press)
     
  • Time Series Forecasting for Self-Aware Systems. Bauer, André; Züfle, Marwin; Herbst, Nikolas; Zehe, Albin; Hotho, Andreas; Kounev, Samuel; in Proceedings of the IEEE (2020). 108(7) 1068–1093.
     

Full Papers

  • Machine Learning Model Update Strategies for Hard Disk Drive Failure Prediction. Züfle, Marwin; Erhard, Florian; Kounev, Samuel; in 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2021).
    (to appear)
     
  • Recommendations for Data-Driven Degradation Estimation with Case Studies from Manufacturing and Dry-Bulk Shipping. Finke, Nils; Mohr, Marisa; Lontke, Alexander; Züfle, Marwin; Kounev, Samuel; Möller, Ralf; in Research Challenges in Information Science (RCIS) (2021). 189–204. Springer.
     
  • A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. Züfle, Marwin; Agne, Joachim; Grohmann, Johannes; Dörtoluk, Ibrahim; Kounev, Samuel; in Proceedings of the 21st IEEE IES International Conference on Industrial Informatics (2021). IEEE.
    (to appear)
     
  • Libra: A Benchmark for Ti... - Download
    Libra: A Benchmark for Time Series Forecasting Methods. Bauer, André; Züfle, Marwin; Eismann, Simon; Grohmann, Johannes; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021). ACM, New York, NY, USA.
     
  • To Fail Or Not To Fail: P... - Download
    To Fail Or Not To Fail: Predicting Hard Disk Drive Failure Time Windows. Züfle, Marwin; Krupitzer, Christian; Erhard, Florian; Grohmann, Johannes; Kounev, Samuel; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020). 19–36. Springer, Cham.
     
  • Autonomic Forecasting Met... - Download
    Autonomic Forecasting Method Selection: Examination and Ways Ahead. Züfle, Marwin; Bauer, André; Lesch, Veronika; Krupitzer, Christian; Herbst, Nikolas; Kounev, Samuel; Curtef, Valentin; in Proceedings of the 16th IEEE International Conference on Autonomic Computing (ICAC) (2019). IEEE.
     

Short Papers

  • A Framework for Time Seri... - Download
    A Framework for Time Series Preprocessing and History-based Forecasting Method Recommendation. Züfle, Marwin; Kounev, Samuel; in Proceedings of the 15th Conference on Computer Science and Information Systems (FedCSIS): Data Mining Competition of the International Symposium on Advanced Artificial Intelligence in Applications (2020).
     
  • Telescope: An Automatic F... - Download
    Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field. Bauer, André; Züfle, Marwin; Herbst, Nikolas; Kounev, Samuel; Curtef, Valentin; in Proceedings of the 36th International Conference on Data Engineering (ICDE) (2020).
     
  • An Automated Forecasting ... - Download
    An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. Bauer, André; Züfle, Marwin; Grohmann, Johannes; Schmitt, Norbert; Herbst, Nikolas; Kounev, Samuel; in Proceedings of the ACM/SPEC International Conference on Performance Engineering (2020). 48–55. Association for Computing Machinery (ACM), New York, NY, USA.
     
  • Telescope: A Hybrid Forec... - Download
    Telescope: A Hybrid Forecast Method for Univariate Time Series. Züfle, Marwin; Bauer, André; Herbst, Nikolas; Curtef, Valentin; Kounev, Samuel; in Proceedings of the International work-conference on Time Series (ITISE 2017) (2017).
     

Book Chapters

  • Towards a Self-Aware Prediction of Critical States. Züfle, Marwin; in Organic Computing: Doctoral Dissertation Colloquium 2020, S. Tomforde, C. Krupitzer (eds.) (2020). 139–155. Kassel University Press GmbH.
     

Workshop Papers

  • A Concept for Crowd-sensed Prediction of Mobile Network Connectivity. Herrnleben, Stefan; Zeidler, Bernd; Züfle, Marwin; Krupitzer, Christian; Kounev, Samuel; in GI/ITG Workshop on Machine Learning in the Context of Communication Networks 2020 (2020).
     
  • Utilizing Clustering to O... - Download
    Utilizing Clustering to Optimize Resource Demand Estimation Approaches. Grohmann, Johannes; Eismann, Simon; Bauer, Andre; Zuefle, Marwin; Herbst, Nikolas; Kounev, Samuel; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 134–139. IEEE.
     

Tutorial Papers

  • Best Practices for Time S... - Download
    Best Practices for Time Series Forecasting. Bauer, André; Züfle, Marwin; Herbst, Nikolas; Kounev, Samuel; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019).
     

Talks

  • Artificial Intelligence in Medicine - From Data Collection to Prediction. Züfle, Marwin; Leppich, Robert; (2019, November).
     
  • Predictive Maintenance fo... - Download
    Predictive Maintenance for Industry 4.0. Züfle, Marwin; (2018, April).
     

Techreports

  • A Survey on Predictive Ma... - Download
    A Survey on Predictive Maintenance for Industry 4.0 Krupitzer, Christian; Wagenhals, Tim; Züfle, Marwin; Lesch, Veronika; Schäfer, Dominik; Mozaffarin, Amin; Edinger, Janick; Becker, Christian; Kounev, Samuel; (2020). Universität Würzburg and University of Mannheim and Syntax Systems GmbH and MOZYS Engineering GmbH.
     
  • A Survey on Human Machine... - Download
    A Survey on Human Machine Interaction in Industry 4.0 Krupitzer, Christian; Müller, Sebastian; Lesch, Veronika; Züfle, Marwin; Edinger, Janick; Lemken, Alexander; Schäfer, Dominik; Kounev, Samuel; Becker, Christian; (2020). Universität Würzburg and University of Mannheim and ioxp GmbH and Syntax Systems GmbH.