International Journal for Uncertainty Quantification
Выходит 6 номеров в год
ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099
IF:
1.7
5-Year IF:
1.9
Immediacy Index:
0.5
Eigenfactor:
0.0007
JCI:
0.5
SJR:
0.584
SNIP:
0.676
CiteScore™::
3
H-Index:
25
Indexed in
Том 6, 2016 Выпуск 4
DOI: 10.1615/Int.J.UncertaintyQuantification.v6.i4
A PRIORI ERROR ANALYSIS OF STOCHASTIC GALERKIN PROJECTION SCHEMES FOR RANDOMLY PARAMETRIZED ORDINARY DIFFERENTIAL EQUATIONS
pp. 287-312
DOI: 10.1615/Int.J.UncertaintyQuantification.2016015843
SURROGATE MODELING FOR STOCHASTIC DYNAMICAL SYSTEMS BY COMBINING NONLINEAR AUTOREGRESSIVE WITH EXOGENOUS INPUT MODELS AND POLYNOMIAL CHAOS EXPANSIONS
pp. 313-339
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016603
TRANSITIONAL ANNEALED ADAPTIVE SLICE SAMPLING FOR GAUSSIAN PROCESS HYPER-PARAMETER ESTIMATION
pp. 341-359
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018590
NOVEL SINGLE-VALUED NEUTROSOPHIC AGGREGATED OPERATORS UNDER FRANK NORM OPERATION AND ITS APPLICATION TO DECISION-MAKING PROCESS
pp. 361-375
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018603
Последний выпуск
Статьи, принятые к публикации
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS
Application of global sensitivity analysis for identification of probabilistic design spaces
Stochastic Galerkin method and port-Hamiltonian form for linear first-order ordinary differential equations
Analysis of the Challenges in Developing Sample-Based Multi-fidelity Estimators for Non-deterministic Models