The experimental design methodology is widely used to quantify uncertainty in the oil and gas industry. This technique is adapted for uncertainty quantification on non-spatial parameters, such as bubble point pressure, oil viscosity, and aquifer strength. However, it is not well adapted for the case of geostatistical (spatial) uncertainty, due to the discrete nature of many input parameters as ...

Risk assessment is a popular and important tool in decision making process. Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty. Here, we consider that model parameters are affected by epistemic uncertainty. To represent epistemic uncertainty in general triangular fuzzy number or trapezoidal fuzzy numbers are u...

Reference Tomm a s Svoboda and Peter Sturm. A badly calibrated camera in ego-motion estimation, propagation of uncertainty. Abstract. This paper deals with the ego-motion estimation (motion of the camera) from two views. To estimate an ego-motion we have to nd correspondences and we need a calibrated camera. In this paper we solve the problem how to propagate known camera calibration errors int...

We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO(2) flux until 2090. The terrestrial sink increases rapidly and the increase is stronger in the presence of climate change. Using a linearized model, we calculate the uncertainty in the flux owing to uncertainty in model parameters. The uncertainty is large and is dominated by the impact of soil moisture on ...

Propagation of errors, in conjunction with the theoretical signal equation for spoiled gradient echo pulse sequences, is used to derive a theoretical expression for uncertainty in quantitative variable flip angle T(1) mapping using two flip angles. This expression is then minimized to derive a rigorous expression for optimal flip angles that elucidates a commonly used empirical result. The theo...

The parameters estimated by Structure from Motion (SFM) contain inherent indeterminacies which we call gauge freedoms. Under a perspective camera, shape and motion parameters are only recovered up to an unknown similarity transformation. In this paper we investigate how covariance-based uncertainty can be represented under these gauge freedoms. Past work on uncertainty modeling has implicitly i...

The robust portfolio selection problems have recently been studied by several researchers (e.g., see [15, 14, 17, 25]). In their work, the “separable” uncertainty sets of the problem parameters (e.g., mean and covariance of the random returns) were considered. These uncertainty sets share two common drawbacks: i) the actual confidence level of the uncertainty set is unknown, and it can be much ...

The parameters estimated by Structure from Motion (SFM) contain inherent indeterminacies which we call gauge freedoms. Under a perspective camera, shape and motion parameters are only recovered up to an unknown similarity transformation. In this paper we investigate how covariance-based uncertainty can be represented under these gauge freedoms. Past work on uncertainty modeling has implicitly i...