PhD student since october 2017,
Under the supervision of Arthur Vidard, Élise Arnaud, Laurent Debreu
Parameter control in the presence of uncertainties
Abstract : Many physical phenomena are modelled numerically in order to better understand and/or to predict their behavior. However, some complex and small scale phenomena can not be fully represented in the models. The introduction of ad-hoc correcting terms is usually the solution to represent these unresolved processes, but those need to be properly estimated.
A good example of this type of problem is the estimation of bottom friction parameters of the ocean floor. This task is further complicated by the presence of uncertainties in certain other characteristics linking the bottom and the surface (eg boundary conditions).
Classical methods of parameter estimation usually imply the minimization of an objective function, that measures the error between some observations and the results obtained by a numerical model. The optimum is directly dependent on the fixed nominal value given to the uncertain parameter ; and therefore may not be relevant in other conditions.
Strategies taking into account those uncertainties will be presented and applied on an academic model of a coastal area, in order to find an optimal value in a robust sense.
Keywords: Robust optimization ; Bayesian inference ; Design of computer experiments ; multiobjective optimization
Supervisors: Arthur Vidard, Élise Arnaud, Laurent Debreu
700 avenue centrale,
victor [dot] trappler [at] univ-grenoble-alpes [dot] fr
120 previsional hours of teaching:
- Sept. – Dec 2017: Computer work: statistics applied to biology. L2 Biology (2 Groups)
- Jan. – May 2018: Calculus. L1 Mathematics applied to humanities and economics
- Sept. – Dec 2018: Computer work: statistics applied to biology. L2 Biology (2 Groups)
- Sept. – Nov. 2018: Geometry and Algebra: Elementary mathematics for physics. L1 Physics