Search results for "Space time"
showing 10 items of 69 documents
A space-time rainfall generator for highly convective Mediterranean rainstorms
2003
Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rai…
The space-time relationship of taxonomic diversity and morphological disparity in the Middle Jurassic ammonite radiation.
2007
14 pages; International audience; The Middle Jurassic ammonite radiation (from the late Aalenian to the end of the mid-Bathonian) is traced using combined analyses of morphological disparity and taxonomic diversity. The global signals of disparity and diversity are compared. These signals are then broken down by paleogeographical provinces to detect any heterogeneity in the radiation. An examination of the global signals reveals three biodiversity crises (discordances between signals) where morphological disparity grows while taxonomic diversity declines. The subdivision of the signals indicates the radiation was heterogeneous between provinces: the global signal is an aggregate of signals …
Financial contagion through space-time point processes
2020
AbstractWe propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The proposal extends network models, recently introduced to model financial contagion, in a space-time point process perspective. The extension helps to improve the assessment of credit risk of an institution, taking into account contagion spillover effects.
The Calderón Problem for a Space-Time Fractional Parabolic Equation
2020
In this article we study an inverse problem for the space-time fractional parabolic operator $(\partial_t-\Delta)^s+Q$ with $0<s<1$ in any space dimension. We uniquely determine the unknown bounded...
Functional Type Error Control for Stabilised Space-Time IgA Approximations to Parabolic Problems
2018
The paper is concerned with reliable space-time IgA schemes for parabolic initial-boundary value problems. We deduce a posteriori error estimates and investigate their applicability to space-time IgA approximations. Since the derivation is based on purely functional arguments, the estimates do not contain mesh dependent constants and are valid for any approximation from the admissible (energy) class. In particular, they imply estimates for discrete norms associated with stabilised space-time IgA approximations. Finally, we illustrate the reliability and efficiency of presented error estimates for the approximate solutions recovered with IgA techniques on a model example.
Guaranteed error bounds and local indicators for adaptive solvers using stabilised space–time IgA approximations to parabolic problems
2019
Abstract The paper is concerned with space–time IgA approximations to parabolic initial–boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of such type of approximations and investigate their efficiency. The derivation of error estimates is based on the analysis of the corresponding integral identity and exploits purely functional arguments in the maximal parabolic regularity setting. The estimates are valid for any approximation from the admissible (energy) class and do not contain mesh-dependent constants. They provide computable and fully guaranteed error bounds for the norms arising in stabilised space–time approximations. Further…
Optical Fibers Enter a New Space-Time Era
2016
We show experimentally a new type of parametric instability associated with the original phenomenon of beam self-cleaning in multimode fibers. Our experimental results are in good agreement with numerical solutions of the Gross-Pitaevskii equation.
A Space-Time Meshless Method for Heat Transfer Problems With High Discontinuities
2013
The aim of this research is the development of a space-time driscretization method based on Diffuse Approximation Meshless method. This method, devoted to transient heat transfer problems presenting high temporal discontinuities, avoids any Finite-Difference time stepping procedure. The space-time discretization proposed here seems to be convenient for continuous transient heat transfer. Nevertheless, for problems including temporal discontinuities, some spurious oscillations, whose amplitudes depend on source power, appear. A new weight function respecting the principle of causality, based on a modification of the involved node’s selection and a normalisation of the distances, is developed…
Regression imputation for Space-Time datasets with missing values
2009
Data consisting in repeated observations on a series of fixed units are very common in different context like biological, environmental and social sciences, and different terminology is often used to indicate this kind of data: panel data, longitudinal data, time series-cross section data (TSCS), spatio-temporal data. Missing information are inevitable in longitudinal studies, and can produce biased estimates and loss of powers. The aim of this paper is to propose a new regression (single) imputation method that, considering the particular structure and characteristics of the data set, creates a “complete” data set that can be analyzed by any researcher on different occasions and using diff…
Space-Time FPCA Clustering of Multidimensional Curves.
2018
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.