Suicide risk assessment aims to reduce uncertainty in order to focus treatment and supervision on those who are judged to be more likely to die by suicide. In this article we consider recent meta-analytic research that highlights the difference between uncertainty about suicide due to chance factors (aleatory uncertainty) and uncertainty that results from lack of knowledge (epistemic uncertaint...

We argue that people intuitively distinguish epistemic (knowable) uncertainty from aleatory (random) uncertainty and show that the relative salience of these dimensions is reflected in natural language use. We hypothesize that confidence statements (e.g., “I am fairly confident,” “I am 90% sure,” “I am reasonably certain”) communicate a subjective assessment of primarily epistemic uncertainty, ...

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...

This paper presents a comprehensive methodology that combines uncertainty quantification, propagation and robustness-based design optimization using a Bayesian framework. Two types of epistemic uncertainty regarding model inputs/parameters are emphasized: (1) uncertainty modeled as p-box, and (2) uncertainty modeled as interval data. A Bayesian approach is used to calibrate the uncertainty mode...

The performance of a multidisciplinary system is inevitably affected by various sources of uncertainties, usually categorized as aleatory (e.g. input variability) or epistemic (e.g. model uncertainty) uncertainty. In the framework of design under uncertainty, all sources of uncertainties should be aggregated to assess the uncertainty of system quantities of interest (QOIs). In a multidisciplina...

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 ...

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and he...

During mathematical simulation of real manufacturing system we can meet any type and rate model uncertainty. Its reasons can be incognizance of modelers or data inaccuracy. So, classification of uncertainties, with respect to they sources, distinguishes between aleatory and epistemic ones. The aleatory uncertainty is an inherent data variation associated with the investigated system or the envi...

The goal of high-level information fusion is to provide effective decision-support regarding situations, e.g., relations between events. One of the main ways that has been proposed in order to achieve this is to reduce uncertainty regarding the situation by utilizing multiple sources of information. There exist two types of uncertainty: aleatory and epistemic. Aleatory uncertainty, also known a...