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 6
DOI: 10.1615/Int.J.UncertaintyQuantification.v6.i6
EMPIRICAL EVALUATION OF BAYESIAN OPTIMIZATION IN PARAMETRIC TUNING OF CHAOTIC SYSTEMS
pp. 467-485
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016645
A CROSS-ENTROPY METHOD ACCELERATED DERIVATIVE-FREE RBDO ALGORITHM
pp. 487-500
DOI: 10.1615/Int.J.UncertaintyQuantification.2016017305
FORWARD AND INVERSE UNCERTAINTY QUANTIFICATION USING MULTILEVEL MONTE CARLO ALGORITHMS FOR AN ELLIPTIC NONLOCAL EQUATION
pp. 501-514
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018661
A NEW INVERSE METHOD FOR THE UNCERTAINTY QUANTIFICATION OF SPATIALLY VARYING RANDOM MATERIAL PROPERTIES
pp. 515-531
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018673
SCENARIO DISCOVERY WORKFLOW FOR ROBUST PETROLEUM RESERVOIR DEVELOPMENT UNDER UNCERTAINTY
pp. 533-559
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018932
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