Browsing by Subject "Stochastic models"
Now showing items 1-20 of 27
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Advances in stochastic models of manufacturing and service operations
(2015)The special issue on advances in stochastic models of manufacturing and service operations presents state-of-the art research results in the area of stochastic models for the analysis, design, coordination, and control of ... -
Bayesian Hierarchical Models for Uncertainty Quantification in Structural Dynamics
(2014)The Bayesian framework for hierarchical modeling is applied to quantify uncertainties, arising mainly due to manufacturing variability, for a group of identical structural components. Parameterized Gaussian models of ... -
Bayesian uncertainty quantification and propagation in molecular dynamics simulations
(2012)A comprehensive Bayesian probabilistic framework is developed for quantifying and calibrating the uncertainties in the parameters of the models (e.g. force-field potentials) involved in molecular dynamics (MD) simulations ... -
Bayesian uncertainty quantification and propagation in nonlinear structural dynamics
(2013)A Bayesian uncertainty quantification and propagation (UQ&P) framework is presented for identifying nonlinear models of dynamic systems using vibration measurements of their components. The measurements are taken to be ... -
A delay-resilient and quality-aware mechanism over incomplete contextual data streams
(2016)We study the case of scheduling a Contextual Information Process (CIP) over incomplete multivariate contextual data streams coming from sensing devices in Internet of Things (IoT) environments. CIPs like data fusion, concept ... -
Efficient techniques for bayesian inverse modeling of large-order computational models
(2013)Bayesian tools for inverse modeling are based on asymptotic approximations and Stochastic Simulation Algorithms (SSA). Such tools require a number of moderate to large number of system re-analyses. For large-order numerical ... -
Experimental validation of the Kalman-type filters for online and real-time state and input estimation
(2017)In this study, a novel dual implementation of the Kalman filter proposed by Eftekhar Azam et al. (2014, 2015) is experimentally validated for simultaneous estimation of the states and input of structural systems. By means ... -
Fast Bayesian structural damage localization and quantification using high fidelity FE models and CMS techniques
(2012)Bayesian estimators are proposed for damage identification (localization and quantification) of civil infrastructure using vibration measurements. The actual damage occurring in the structure is predicted by Bayesian model ... -
A hybrid downscaling approach for the estimation of climate change effects on droughts using a geo-information tool. Case study: Thessaly, Central Greece
(2016)Multiple linear regression is used to downscale large-scale outputs from CGCM2 (second generation CGCM of Canadian centre for climate monitoring and analysis) and ECHAM5 (developed at the Max Planck Institute for Meteorology), ... -
Implementation of an adaptive meta-model for Bayesian finite element model updating in time domain
(2017)This work explores the feasibility of integrating an adaptive meta-model into a finite element model updating formulation using dynamic response data. A Bayesian model updating approach based on a stochastic simulation ... -
Joint quantizer optimization for scalable coding
(2010)Scalability is an attractive solution to the problems posed by modern multimedia transmission systems. The key for better performance in scalable coding is joint rate distortion optimization. We present a new stochastic ... -
Model-reduction techniques for reliability-based design problems of complex structural systems
(2016)This work presents a strategy for dealing with reliability-based design problems of a class of linear and nonlinear finite element models under stochastic excitation. In general, the solution of this class of problems is ... -
New results on turbulence modeling for free-space optical systems
(2010)In this paper, we propose a statistical channel model, named as Double-Weibull, to describe the irradiance fluctuations in moderate and strong turbulence for free-space optical (FSO) systems. The proposed stochastic model ... -
Output-only schemes for joint input-state-parameter estimation of linear systems
(2015)The subject of predicting structural response, for control or fatigue assessment purposes, via output only vibration measurements is an emerging topic of Structural Health Monitoring. The subject of estimation of the states ... -
Planning of dynamic mobile optical virtual network infrastructures supporting cloud services
(2014)This paper proposes a next generation ubiquitous converged infrastructure to support Cloud and mobile Cloud computing services. The proposed infrastructure facilitates interconnection of fixed and mobile end users with ... -
Proactive & Time-Optimized Data Synopsis Management at the Edge
(2022)Internet of Things offers the infrastructure for smooth functioning of autonomous context-aware devices being connected towards the Cloud. Edge Computing (EC) relies between the IoT and Cloud providing significant advantages. ... -
Probabilistic method for estimation of spinning reserves in multi-connected power systems with Bayesian network-based rescheduling algorithm
(2019)This study proposes a new stochastic spinning reserve estimation model applicable to multi-connected energy systems with reserve rescheduling algorithm based on Bayesian Networks. The general structure of the model is ... -
Reliability analysis of dynamical systems
(2019)The use of reduced-order models in the context of reliability analysis of dynamical systems under stochastic excitation is explored in this chapter. A stochastic excitation model based on a point-source model is introduced, ... -
Reliability sensitivity analysis of dynamical systems
(2019)The reliability sensitivity analysis of systems subjected to stochastic loading is considered in this chapter. In particular, the change that the probability of failure undergoes due to changes in the distribution parameters ... -
Reliability sensitivity analysis of stochastic finite element models
(2015)This contribution presents a scheme for integrating a model reduction technique into a simulation-based method for reliability sensitivity analysis of a class of medium/large nonlinear finite element models under stochastic ...