High-Level Information Fusion (HLIF) utilizes techniques from Low-Level Information Fusion (LLIF) to support situation/impact assessment, user involvement, and mission and resource management (SUM). Given the unbounded analysis of situations, events, users, resources, and missions; it is obvious that uncertainty is manifested by the nature of application requirements. In this panel, we seek dis...

Doug, Will and I are on the same page about the need for quantitative models to address this problem, and I commend them for taking this forward. However, at the last SWG meeting on 13 January I felt that Doug made claims about his and Will’s modeling approach that I felt were not warranted. The first was that they are fully accounting for all sources of uncertainty. An important source of unce...

This report briefly summarizes the discussions carried out in the working group on classification, representation and modeling of uncertain data. The discussion was divided into two subgroups: the first subgroup studied how different representation and modeling alternatives currently proposed can fit in a bigger picture of theory and technology interaction, while the second subgroup focused on ...

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with a...

A complex system usually encompasses agents, as they are known from modern Artificial Intelligence. Within the system dynamics, interactions between agents are affected by perturbations (uncertainty), which often make modeling difficult. This paper introduces a modeling approach based on a function that quantifies uncertainty: the fuzzy measure of ambiguity. A model based on ambiguity minimizat...

in this paper the fuzzy structural reliability index was determined through modeling epistemic uncertainty arising from ambiguity in statistical parameters of random variables. the first order reliability method (form) has been used and a robust genetic algorithm in the alpha level optimization method has been proposed for the determination of the fuzzy reliability index. the sensitivity level ...

The objective of finance theory is to predict the future evolution of financial quantities, such as the price of a single asset or broad market movements. Uncertainty as to the future evolution of prices is a fundamental tenet of modern finance theory. The paradigm of choice for modeling uncertainty in finance is the probability theory. This tutorial presents the formal probabilistic concepts b...

An Analysis of the Total Insensitivity of Input Shaping Designs Lucy Y. Pao Electrical and Computer Engineering Department University of Colorado Boulder, Colorado 80309{0425 Abstract In the modeling of exible structures, there is generally uncertainty in both the frequencies and damping constants, and it is thus important that the control methods for such systems be robust to these uncertainti...

Existing procedures for model validation have been deemed inadequate for many engineering systems. The reason of this inadequacy is due to the high degree of complexity of the physical mechanisms that govern these systems. It is proposed in this paper to shift the attention from modeling the engineering system itself to modeling the uncertainty that underlies its behavior. A mathematical framew...

Multi-stage optimization under uncertainty techniques can be used to solve long-term management problems. Although many optimization modeling language extensions as well as computational environments have been proposed, the acceptance of this technique is generally low, due to the inherent complexity of the modeling and solution process. In this paper a simplification to annotate multi-stage de...