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
MODEL ERROR ESTIMATION USING PEARSON SYSTEM WITH APPLICATION TO NONLINEAR WAVES IN COMPRESSIBLE FLOWS
DECISION THEORETIC BOOTSTRAPPING
UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING
STOCHASTIC GALERKIN METHOD AND PORT-HAMILTONIAN FORM FOR LINEAR FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS
Статьи, принятые к публикации
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS
Application of global sensitivity analysis for identification of probabilistic design spaces
SENSITIVITY ANALYSES OF A MULTI-PHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS
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