Parcourir par sujet "Uncertainty"
Voici les éléments 1-20 de 31
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Application of a One-Dimensional Computational Model for the Prediction of Deposition from a Dry Powder Inhaler
(2017)Background: Accurate prediction of the regional deposition of inhaled dry powders as a function of powder properties and breathing pattern is a long-term research goal for pulmonary drug delivery. In the present work, ... -
Application of single-drop microextraction coupled with gas chromatography for the determination of multiclass pesticides in vegetables with nitrogen phosphorus and electron capture detection
(2009)In the present work the single-drop microextraction (SDME) technique coupled with GC-NPD and GC-ECD was evaluated for the determination of multi-class pesticides in vegetables. The donor sample solution preparation was ... -
Bayesian uncertainty quantification for machine-learned models in physics
(2022)Being able to quantify uncertainty when comparing a theoretical or computational model to observations is critical to conducting a sound scientific investigation. With the rise of data-driven modelling, understanding various ... -
Data-driven inference of the reproduction number for COVID-19 before and after interventions for 51 European countries
(2020)The reproduction number is broadly considered as a key indicator for the spreading of the COVID-19 pandemic. Its estimated value is a measure of the necessity and, eventually, effectiveness of interventions imposed in ... -
Dynamic vehicle routing under uncertain travel costs and refueling opportunities
(2019)We study the vehicle routing problem for a system where there is some uncertainty regarding both the cost of travel and the refueling opportunities. Travel cost stands for the energy spent by the vehicle to move between ... -
Effects of spatial variability of soil properties and ground motion characteristics on permanent displacements of slopes
(2022)The seismic performance of earth slopes is a problem of great importance in geotechnical earthquake engineering associated with various sources of uncertainty. This research investigates the effects of two important causes ... -
Fuzzy cognitive map-based modeling of social acceptance to overcome uncertainties in establishing waste biorefinery facilities
(2018)Sustainable Waste Biorefinery Facilities (WBFs) represent multifactorial systems that necessitate the organization, cooperation and the acceptance of different social stakeholders. However, these attempts have become targets ... -
Fuzzy Pooling
(2021)Convolutional neural networks (CNNs) are artificial learning systems typically based on two operations: convolution, which implements feature extraction through filtering, and pooling, which implements dimensionality ... -
HIERARCHICAL BAYESIAN INFERENCE FOR QUANTIFICATION OF UNCERTAINTY IN MULTI LEVEL MODELS OF DYNAMICAL SYSTEMS
(2021)Calibration of model parameters is increasingly playing a key role in the process of accurately predicting the responses of full-scale dynamical systems. Such systems often exhibit complexities arising from the assembling ... -
Hierarchical Bayesian learning framework for multi-level modeling using multi-level data
(2022)A hierarchical Bayesian learning framework is proposed to account for multi-level modeling in structural dynamics. In multi-level modeling the system is considered as a hierarchy of lower-level models, starting at the ... -
Hierarchical Bayesian Model Updating for Nonlinear Structures Using Response Time Histories
(2022)This paper presents a novel hierarchical Bayesian modeling (HBM) framework for the model updating and response predictions of dynamic systems with material nonlinearity using multiple data sets consisting of measured ... -
Hierarchical Bayesian model updating for structural identification
(2015)A new probabilistic finite element (FE) model updating technique based on Hierarchical Bayesian modeling is proposed for identification of civil structural systems under changing ambient/environmental conditions. The ... -
Hierarchical Bayesian modeling framework for model updating and robust predictions in structural dynamics using modal features
(2022)The hierarchical Bayesian modeling (HBM) framework has recently been developed to tackle the uncertainty quantification and propagation in structural dynamics inverse problems. This new framework characterizes the ensemble ... -
Human thermophysiological models: Quantification of uncertainty in the output quantities of the passive system due to uncertainties in the control equations of the active system via the Monte Carlo method
(2021)Uncertainty propagation analysis in the Fiala thermophysiological model is performed by the Monte Carlo Method. The uncertainties of the output quantities of the passive system, due to imported uncertainties in the ... -
Input-state-parameter estimation of structural systems from limited output information
(2019)A successive Bayesian filtering framework for addressing the joint input-state-parameter estimation problem is proposed in this study. Following the notion of analytical, rather than hardware redundancy, the envisaged ... -
Nonlinear model updating through a hierarchical Bayesian modeling framework
(2022)A new time-domain probabilistic technique based on hierarchical Bayesian modeling (HBM) framework is proposed for calibration and uncertainty quantification of hysteretic type nonlinearities of dynamical systems. Specifically, ... -
A Novel Requirements Prioritization Approach based on 360 Degree Feedback and Group Recommendation
(2021)Requirements' prioritization (RP) is an important activity in software development and a crucial step towards making proper decisions for the software release planning. RP is performed by various categories of stakeholders, ... -
Optimal Experimental Design Methodology for Parameter Estimation of Nonlinear Models
(2021)Experimental data are used to improve structural models and model-based predictions of output quantities of interest (QoI), that are crucial in making decisions regarding structural health, safety and performance. The ... -
Risk analysis framework for the optimum remediation of a contaminated aquifer under uncertainty: application in Lake Karla aquifer, Thessaly, Greece
(2022)A risk analysis framework is proposed for the optimum remediation of a contaminated aquifer under hydrogeological uncertainty. The limited information and the spatial variation of hydraulic conductivity in a real-world ... -
Robust optimal sensor configuration using the value of information
(2022)Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for ...
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