Michael Hanss

About Michael Hanss

Michael Hanss, With an exceptional h-index of 21 and a recent h-index of 14 (since 2020), a distinguished researcher at Universität Stuttgart, specializes in the field of Uncertainty Quantification, Possibility Theory, Fuzzy Arithmetic, (Nonlinear) Oscillations.

His recent articles reflect a diverse array of research interests and contributions to the field:

Distinguishing geometrically identical instruments: Possibilistic identification of material parameters in a parametrically model order reduced finite element model of a …

Uncertainty quantification of large-scale dynamical systems using parametric model order reduction

Analysis of mixed uncertainty through possibilistic inference by using error estimation of reduced order surrogate models

A Practical Strategy for Valid Partial Prior-Dependent Possibilistic Inference

A universal approach to imprecise probabilities in possibility theory

An advanced sampling technique for possibilistic uncertainty propagation

A Recursive Formulation of Possibilistic Filters

Dependent possibilistic arithmetic using copulas

Michael Hanss Information

University

Position

Germany

Citations(all)

3491

Citations(since 2020)

1186

Cited By

2784

hIndex(all)

21

hIndex(since 2020)

14

i10Index(all)

44

i10Index(since 2020)

23

Email

University Profile Page

Google Scholar

Michael Hanss Skills & Research Interests

Uncertainty Quantification

Possibility Theory

Fuzzy Arithmetic

(Nonlinear) Oscillations

Top articles of Michael Hanss

Title

Journal

Author(s)

Publication Date

Distinguishing geometrically identical instruments: Possibilistic identification of material parameters in a parametrically model order reduced finite element model of a …

Journal of Sound and Vibration

Alexander Brauchler

Dominik Hose

Pascal Ziegler

Michael Hanss

Peter Eberhard

2022/9/29

Uncertainty quantification of large-scale dynamical systems using parametric model order reduction

Mechanical Systems and Signal Processing

Benjamin Fröhlich

Dominik Hose

Oliver Dieterich

Michael Hanss

Peter Eberhard

2022/5/15

Analysis of mixed uncertainty through possibilistic inference by using error estimation of reduced order surrogate models

Tom Könecke

Dominik Hose

Lennart Frie

Michael Hanss

Peter Eberhard

2022

A Practical Strategy for Valid Partial Prior-Dependent Possibilistic Inference

Dominik Hose

Michael Hanss

Ryan Martin

2022/9/30

A universal approach to imprecise probabilities in possibility theory

International Journal of Approximate Reasoning

Dominik Hose

Michael Hanss

2021/6/1

An advanced sampling technique for possibilistic uncertainty propagation

Mechanical Systems and Signal Processing

Markus Mäck

Michael Hanss

2021/1/15

A Recursive Formulation of Possibilistic Filters

Dominik Hose

Michael Hanss

2021/8/18

Dependent possibilistic arithmetic using copulas

Ander Gray

Dominik Hose

Marco De Angelis

Michael Hanss

Scott Ferson

2021/6/16

On the solution of forward and inverse problems in possibilistic uncertainty quantification for dynamical systems

Dominik Hose

Michael Hanss

2020

Possibilistic Investigation of Mechanical Control Systems Under Uncertainty

Andreas Hofmann

Michael Hanss

Peter Eberhard

2020

See List of Professors in Michael Hanss University(Universität Stuttgart)