This image shows Dominik Hose

Dominik Hose

M.Sc.

Institute of Engineering and Computational Mechanics

Contact

+49 711 685 68242
+4971168566400

Pfaffenwaldring 9
70569 Stuttgart
Deutschland
Room: 4.157

Subject

Development of Possibilistic Filter Design Methods for State Estimation in Dynamical Systems under Uncertainty

  • Hose, D.: Possibilistic Reasoning with Imprecise Probabilities: Statistical Inference and Dynamic Filtering. Dissertation, 2022. (submitted)
     
  • Könecke, T.; Hose, D.; Frie, L.; Hanss, M.; Eberhard, P.: Analysis of Mixed Uncertainty through Possibilistic Inference by using Error Estimation of Reduced Order Surrogate Models. Proceedings of the 9th International Conference on Uncertainties in Structural Dynamics USD 2022, KU Leuven (Belgium), September 12-14, 2022. (submitted)
     
  • Brauchler, A; Hose, D.; Ziegler, P.; Hanss, M.; Eberhard, P.: Distinguishing Geometrically Identical Instruments: Possibilistic Identification of Material Parameters in a Parametrically Model Order Reduced Finite Element Model of a Classical Guitar. Journal of Sound and Vibration, 2022. (submitted)
     
  • Gray, A.; Hose, D.; De Angelis, M.; Hanss, M.; Ferson, S.: Dependent Possibilistic Arithmetic Using Copulas. Proceedings of Machine Learning Research, Volume 147, 2021, pp. 180-190
     
  • Hose, D.; Hanss, M.: A Recursive Formulation of Possibilistic Filters. Proceedings of Machine Learning Research, Volume 147, 2021, pp. 169-179
     
  • Hose, D.; Hanss, M.: A Universal Approach to Imprecise Probabilities in Possibility Theory. International Journal of Approximate Reasoning, Volume 133, 2021, pp. 133-158.
    [ DOI: 10.1016/j.ijar.2021.03.010 ]
     
  • Fröhlich, B.; Hose, D.; Dieterich, O.; Hanss, M.; Eberhard, P.: Uncertainty Quantification of Large-Scale Dynamical Systems Using Parametric Model Order Reduction, 2020. (submitted for publication)
     
  • Hose, D.; Hanss, M.: On the Solution of Forward and Inverse Problems in Possibilistic Uncertainty Quantification for Dynamical Systems. Proceedings of the 9th International Workshop on Reliable Engineering Computing REC 2021, Taormina (Italy), May 16-20 2021, pp. 295 ff.
    [ Link ] [ Preprint ]
     
  • Hose, D.; Hanss, M.: On Data-Based Estimation of Possibility Distributions. Fuzzy Sets and Systems, Volume 399, 2020, pp. 77-94, ISSN 0165-0114.
    [ DOI: 10.1016/j.fss.2020.03.017 ] [ Preprint ]
     
  • Hose, D.; Hanss, M.: Possibilistic calculus as a conservative counterpart to probabilistic calculus. Mechanical Systems and Signal Processing, 133:106290, November 2019.
    [ DOI: 10.1016/j.ymssp.2019.106290 ] [ Preprint ]
     
  • Hose, D.; Hanss, M.: Consistent Inverse Probability and Possibility Propagation. Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology EUSFLAT 2019, Prague (Czech Republic), September 9-13 2019.
    [ DOI: 10.2991/eusflat-19.2019.1 ]
     
  • Hose, D.; Mäck, M.; Hanss, M.: Robust Optimization in Possibility Theory. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering, 5(4): 041001, December 2019.
    [ DOI: 10.1115/1.4044037 ]
     
  • Hose, D.; Mäck, M.; Hanss, M.: On Probability-Possibility Consistency in High-Dimensional Propagation Problems. Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering UNCECOMP 2019, Crete (Greece), June 24-26 2019.
    [ DOI: 10.7712/120219.6330.18439 ]
     
  • Hose, D.; Hanss, M.: Towards a General Theory for Data-Based Possibilistic Parameter Inference. Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering UNCECOMP 2019, Crete (Greece), June 24-26 2019.
    [ DOI: 10.7712/120219.6329.18389 ]
     
  • Hose, D.; Hanss, M.: On Inverse Fuzzy Arithmetical Problems in Uncertainty Analysis. Proceedings of the 7th International Conference on Uncertainties in Structural Dynamics USD 2018, KU Leuven (Belgium), September 17-19 2018.
    [ Link ]

  • Hose, D.; Hanss, M.: Possibilistic Identification of Reliable Finite Impulse Response Models. Proceedings of the 8th International Workshop on Reliable Engineering Computing REC 2018, University of Liverpool (England), July 16-18 2018.
    [ Link ]

  • Hose, D.; Hamann, D.; Hanss, M.; Eberhard, P.: A Data-Driven Possibilistic Approach to the Identification of Uncertain Stability Lobe Diagrams. Proceedings in Applied Mathematics and Mechanics, 18: 1-2 e201800087, 2018.
    [DOI: 10.1002/pamm.201800087 ]

  • Hose, D.; Hanss, M.: Fuzzy linear least squares for the identification of possibilistic regression models. Fuzzy Sets and Systems, Volume 367, 2019, Pages 82-95, ISSN 0165-0114.
    [DOI: 10.1016/j.fss.2018.10.003 ]

  • de Prada, C.; Hose, D.; Gutierrez, G.; Pitarch J. L.: Developing Grey-Box Dynamic Process Models. Proceedings of the 9th Vienna International Conference on Mathematical Modelling Mathmod 2018, Vienna (Austria), February 21-23 2018.
    [DOI: 10.1016/j.ifacol.2018.03.088 ]

  • Hose, D.; Mäck, M.; Hanss, M.: A Possibilistic Approach to the Optimization of Uncertain Systems. Proceedings of the 7th International Symposium on Uncertainty Modeling and Analysis ISUMA 2018, Florianopolis (Brazil), April 8-11 2018.
    [ Link ]

  • Mäck, M., Hose, D. and Hanss, M.: On Using Fuzzy Arithmetic in Optimization Problems with Uncertain Constraints. Proceedings in Applied Mathematics and Mechanics, 17: 57–58, 2017.
    [DOI: 10.1002/pamm.201710017 ]

  • Hose, D.: Investigations on the Optimization of Multibody Systems in the Presence of Uncertainty, Masterarbeit MSC-250. Institut für Technische und Numerische Mechanik, Universität Stuttgart, 2017.
    (Supervisors: Hanss, M.; Mäck, M.)

  • Hose, D.; de Prada, C.; Gonzalez, G.: Modeling and Identification of ABE Fermentation Processes. Proceedings of the XXXVII Jornadas de Automática, Universidad Complutense de Madrid (Spain), 2016.
    [ Link (Paper 45) ]
  • November 24, 2021: ITM Statusseminar, Monbachtal. "The Possibilistic Philosophy of Uncertainty Quantification".
     
  • July 8, 2021: 12th International International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA 2021, online). "A Recursive Formulation of Possibilistic Filters".
     
  • June 29, 2021: ITM Workshop on Fuzzy Predictions and Famous, Stuttgart (Germany). "Famous: Software for Fuzzy Uncertainty Quantification in Blackbox Models".
     
  • May 19, 2021: 9th International Workshop on Reliable Engineering Computing (REC 2021, online). "On the Solution of Forward and Inverse Problems in Possibilistic Uncertainty Quantification for Dynamical Systems".
     
  • August 5, 2020: Virtual talk at the Institute for Risk and Uncertainty, University of Liverpool (United Kingdom). "The Embarrassingly Simple Calculus of Possibility Theory".
     
  • September 9, 2019: 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), Prague (Czech Republic). "Consistent Inverse Probability and Possibility Propagation".
     
  • June 24, 2019: 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019), Crete (Greece). "Towards a General Theory for Data-Based Possibilistic Parameter Inference".
     
  • May 4, 2019: ITM Statusseminar, Bad Herrenalb. "Imprecise Probabilities - Making Sense of Inverse Problems in Fuzzy Arithmetic".

  • September 17, 2018: 7th International Conference on Uncertainty in Structural Dynamics (USD 2018), Leuven (Belgium). "On Inverse Fuzzy Arithmetical Problems in Uncertainty Analysis".

  • July 16, 2018: 8th International Workshop on Reliable Engineering Computing (REC 2018), Liverpool (UK). "Possibilistic Identification of Reliable Finite Impulse Response Models".
     
  • May 28, 2018: ITM Statusseminar, Bad Herrenalb. "Possibilistic Identification Problems - How Mechanical Engineering Can Benefit from Fuzzy Set Theory".

  • May 23, 2017: ITM Statusseminar, Monbachtal. "The Inverse Problem of Fuzzy Arithmetic - An Illustrative Introduction".
  • Gray, A.; Hose, D.; De Angelis, M.; Hanss, M.; Ferson, S.: Dependent Possibilistic Arithmetic Using Copulas. 12th International Symposium on Imprecise Probabilities: Theories and Applications (online), 2021.
     
  • Hose, D.; Hanss, M.: A Recursive Formulation of Possibilistic Filters. 12th International Symposium on Imprecise Probabilities: Theories and Applications (online), 2021.
     
  • Hamann, D.; Hose, D.; Eberhard, P.: Parameter Identification Based on Stability Lobe Diagrams of Machining Processes. SimTech Statusseminar, Bad Boll 2017.

  • Hose, D.; de Prada, C.; Gonzalez, G.: Modeling and Identification of ABE Fermentation Processes. XXXVII Jornadas de Automática. Universidad Complutense de Madrid (Spain) 2016.
  • Investigations on the Applicability of Error Estimators for Possibilistic Inference in Parametrically Reduced Surrogate Models of Mechanical Systems, Master thesis. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2021. (ongoing)
    In co-supervision with Lennart Frie, M.Sc.
     
  • Set-Membership Particle Filtering as a Foundation for Robust Control Concepts, SimTech student thesis. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2021.
    In co-supervision with Henrik Ebel, M.Sc.
     
  • Statistical Inference in Parametrically Reduced Surrogate Models of Mechanical Systems on the Basis of Possibility Theory, Master thesis. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2020.
    In co-supervision with Benjamin Fröhlich, M.Sc.
      
  • Identification of Parameter Ranges of Human Simulation Models with Possibilistic Methods and Validation Data of a Driver-in-the-Loop Simulation Study, Bachelor thesis. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2020.
    In co-supervision with Fabian Kempter, M.Sc.
     
  • Implementation of a Parameter Identification Algorithm Based on Impedance Measurements of the Ear, Bachelor thesis BSC-108. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2019.
    In co-supervision with Benjamin Sackmann, M.Sc.
     
  • Object Localization via Particle Filters, SimTech-Seminararbeit SA-19. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2018.
     
  • Comparison of Model-Based and Data-Based Approximations of Mechanical Systems, Student thesis STUD-487. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2018.
    In co-supervision with Benjamin Fröhlich, M.Sc.
     
  • Quantification of Uncertainties in Simplified Mechanical Surrogate Models, Student thesis STUD-486. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2018.
    In co-supervision with Markus Mäck, M.Sc.
     
  • Model Updating of Mechanical Systems Under Polymorphic Uncertainties, Student thesis STUD-484. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2018.
    In co-supervision with Markus Mäck, M.Sc.
     
  • Possibilistic Stability Analysis and Optimal Controller Synthesis of a Dynamical System Under Uncertainty, Master thesis MSC-263. Institute of Engineering and Computational Mechanics, University of Stuttgart, 2018.
    In co-supervision with Andreas Hofmann, M.Sc.
  • Administration of the exchange program with the Georgia Institute of Technology

  • Key administration
     
  • Administration of the FAMOUS software for the analysis of systems under uncertainty
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