Uncertainty Quantification
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Recent papers in Uncertainty Quantification
Through our project, we want to investigate the effect of policy uncertainty on the unemployment level and we expect to find a positive causal effect. An interesting debate has risen recently since many scholars argued that the... more
This paper deals with the applications of stochastic spectral methods for structural topology optimization in the presence of uncertainties. A non-intrusive polynomial chaos expansion is integrated into a topology optimization algorithm... more
ABSTRACT: The present paper examines how statistics of extremes can be used to enhance the assessment and performance prediction of monitored highway bridges. This is achieved by proposing an approach to obtain a monitoring-based... more
A stochastic model of the dynamic behavior of sawn timber beams of Ar- gentinean Eucalyptus grandis is herein presented. The aim of this work is to study the influence of the timber knots in the dynamical response of timber beams. The... more
This chapter is devoted to introducing the theories of interval algebra to people who are interested in applying the interval methods to uncertainty analysis in science and engineering. In view of this purpose, we shall introduce the key... more
Quantitative fire risk analysis aims at providing an assessment of fire safety on a scientific basis and taking relevant uncertainties into account in a rational quantitative manner. Under a probabilistic approach, performance measures... more
The present study was undertaken to develop and validate a simple, sensitive, accurate, precise and reproducible UV spectrophotometric method for cefuroxime axetil using methanol as solvent. In this method the simple UV spectrum of... more
ABSTRACT The Romanesque “tribune” of the abbey church of Cuxa was probably dismantled in the sixteenth century. No description or representation of this work of art, at the time of its existence, is to be found. It is known today... more
This half-day tutorial on Belief function (random sets) for the working scientist was presented on July 9th 2016 at the latest International Joint Conference on Artificial Intelligence (IJCAI-16). The tutorial is very comprehensive (468... more
Is there room enough in all creation for another 'Empty Universe Theory'? How should we view the realm in which we exist? Are the natures of matter and energy, their compositions and relationships with each other the fundamental key to... more
The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably... more
After over 50 years of spaceflight, the calculation of the necessary margin on the thermal protection system of an entering spacecraft remains a largely ad-hoc (in a tactical sense) process governed by engineering judgment. Over the past... more
With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not... more
In this chapter the basic principles of two methodologies for uncertainty quantification (UQ) are discussed, namely the polynomial chaos method and the collocation method. UQ deals with the propagation of uncertainties through complex... more
The single most important statement that can be made with regard to the logical status of human and physical geographical reasoning is that it belongs to the class of non-monotonic reasoning. In other words, geographical reasoning is... more
Uncertainty quantification was conducted using non – intrusive form of Generalised Polynomial Chaos methods for square inline tube bundles. The input was treated as uncertain. Uncertainties were considered in Reynolds number of the flow... more
Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine... more
We begin by constructing the algebra of classical intervals and prove that it is a nondistributive abelian semiring. Next, we formalize the notion of interval dependency, along with discussing the algebras of two alternate theories of... more
The validation of a high-fidelity uncertainty quantification of a high-speed catamaran is presented, with focus on irregular wave analysis and approximation methods used in design optimization studies, namely a deterministic regular wave... more
This study is motivated by the sharp contrast between physical and probabilistic models of civil engineering. The current practice focuses on physical models while probabilistic ones are relatively underdeveloped. This unbalance can even... more
A B S T R A C T Stochastic optimization methods, such as genetic algorithms, search for the global minimum of the misfit function within a given parameter range and do not require any calculation of the gradients of the misfit surfaces.... more
Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty—a property of listeners' prospective state... more
Computer vision is an ever growing discipline whose ambitious goal is to enable machines with the intelligent visual skills humans and animals are provided by Nature, allowing them to interact effortlessly with complex, dynamic... more
Flood management alternatives are often evaluated on the basis of flood parameters such as depth and velocity. As these parameters are uncertain, so is the evaluation of the alternatives. It is thus important to incorporate the... more
Prediction is the key objective of many machine learning applications. Accurate, reliable and robust predictions are essential for optimal and fair decisions by downstream components of artificial intelligence systems, especially in... more
Stringer-to-floor beam connections were reported as one of the most fatigue-prone details in riveted steel railway bridges. To detect stiffness degradation that results from the initiation and growth of fatigue cracks, an automated damage... more
The Novikov–Furutsu (NF) theorem is a well-known mathematical tool, used in stochastic dynamics for correlation splitting, that is, for evaluating the mean value of the product of a random functional with a Gaussian argument multiplied by... more