A seminar at Center for Mathematical Sciences,July 10, Friday,at 4:30pm

Speaker ：He Yanyan (Univ of Utah, USA)

Time：2015年7月10日（星期五）下午4:30

Location：Center for Mathematical Sciences, Room 813（创新研究院恩明楼813室）

Title: Quantifying uncertainty in modeling and simulation is crucial since the parameters of the physical system are inherently non-deterministic and knowledge of the system embodied in the model is incomplete or inadequate. The most well-developed nonadditive-measure theory – the Dempster- Shafer theory of evidence – is explored for uncertainty quantification and propagation. Specifically, we propose the MinMax method to construct belief functions to represent uncertainty in the information (data set) involving the inseparably mixed type of uncertainties; construct belief/probability density functions for the output or the statistics of the output given the belief/probability density functions for the uncertain input variables; propose a robust and comprehensive procedure to combine multiple bodies of evidence in the situation that multiple models are available for the same quantity of interest. The proposed approaches are illustrated using different examples.