Uncertainty Propogation and Applications


Dagum_1993 A Bayesian analysis of simulation algorithms for inference in belief networks

Dempster_2001 Normal belief functions and the Kalman filter (HC)

Haenni_2003 Implementing belief function computations

LeMaitre_2004-1 Uncertainty propogation using Wiener-Haar expansions (HC)

LeMaitre_2004-2 Multi-resolution analysis of Wiener-type uncertainty propogation schemes (HC)

Liu_2003  A linear belief function approach to portfolio evaluation

Liu_2006 Knowledge representation and integration for portfolio evaluation uisng linear belief functions

Luo_1997 Using D-S theory to represent climate change uncertainties

Mozumer_2004   Robust design: uncertainty representation and propogation

Oberkampf_2001 Challenge problems: uncertainty in system response given uncertain parameters

Oberkampf_2005 Evidence theory for engineering applications

Ramasso_2006 A temporal belief filter improving human action recognition in videos

Ramasso_2006a Belief scheduling for recognition of human action sequence

Rao_2005 Uncertainty analysis in atmospheric dispersion modeling

Rombaut_1999 State recognition in discrete dynamical systems using Petri nets and evidence theory

Shenoy_2001 Modeling financial portfolios using belief functions

Swiler_2007 Aleatory and epistemic uncertainty quantification for engineering applications (HC)

Trabelsi_2007 Pruning belief decision tree methods in averaging and conjunctive approaches (HC)

Wu_2002 Sensor fusion using D-S theory

Wu_2003 Sensor fusion using D-S theory II: static weighting and KF-like dynamic weighting

Zohdy_1995 Fused multi-sensor data using a kalman filter modified with interval probability support