We use data from a small aperture array in southern California to quantify variations in source parameter estimates at closely spaced stations (distances ranging from ∼7 to 350 m) to provide constraints on parameter uncertainties. Many studies do not consider uncertainties in these estimates even though they can be significant and have important implications for studies of earthquake source phy...

this paper presents a probabilistic optimal power flow (popf) algorithm considering different uncertainties in a smart grid. different uncertainties such as variation of nodal load, change in system configuration, measuring errors, forecasting errors, and etc. can be considered in the proposed algorithm. by increasing the penetration of the renewable energies in power systems, it is more essent...

a reliability analysis of suspension bridges against buffeting failure due to gustiness of wind velocity is carried out using the concept of pra (probabilistic risk analysis) procedure. for this purpose, the bending stresses at the critical nodes of the bridge deck are obtained for buffeting forces using a spectral analysis technique and a finite element approach. for the purpose of reliability...

image segmentation is an essential issue in image description and classification. currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. moreover, there are many uncertainties and vagueness in images, which crisp clustering and even type-1 fuzzy clustering could not handle. hence, type-...

Libraries of stellar spectra are fundamental tools in the study of stellar populations and in automatic determination of atmospheric parameters for large samples of observed stars. In the context of the present volume, here I give an overview of the current status of stellar spectral libraries from the perspective of stellar population modeling: what we have currently available, how good they a...

Over the last half-century quantitative stellar spectroscopy has made great progress. However, most stellar abundance analyses today still employ rather simplified models, which can introduce severe systematic errors swamping the observational errors. Some of these uncertainties for late-type stars are briefly reviewed here: atomic and molecular data, stellar parameters, model atmospheres and s...

Extinction forecasting is one of the most important and challenging areas of conservation biology. Overestimates of extinction rates or the extinction risk of a particular species instigate accusations of hype and overblown conservation rhetoric. Conversely, underestimates may result in limited resources being allocated to other species/habitats perceived as being at greater risk. In this paper...

This report demonstrates the application of Bayesian networks for modelling and reasoning about uncertainties. A scenario for naval anti-surface warfare is constructed and Bayesian networks are used to represent and update uncertainties encountered in the process of 'situation assessment'. Concepts from information theory are used to provide a measure of uncertainty and understand its flow in a...

What is the magnitude of uncertainties about future greenhouse gas emissions, GDP and emissions intensity of economies? Is there a link between fluctuations in economic activity and fluctuations in emissions? These questions are crucial to understand the extent and composition of cost uncertainty under emissions trading schemes, the degree to which it can be reduced by mechanism design options ...