International Journal for Uncertainty Quantification
Publication de 6 numéros par an
ISSN Imprimer: 2152-5080
ISSN En ligne: 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
Volume 6, 2016 Numéro 5
DOI: 10.1615/Int.J.UncertaintyQuantification.v6.i5
AN IMPROVED SCORE FUNCTION FOR RANKING NEUTROSOPHIC SETS AND ITS APPLICATION TO DECISION-MAKING PROCESS
pp. 377-385
DOI: 10.1615/Int.J.UncertaintyQuantification.2016018441
A UNIFIED FRAMEWORK FOR RELIABILITY ASSESSMENT AND RELIABILITY-BASED DESIGN OPTIMIZATION OF STRUCTURES WITH PROBABILISTIC AND NONPROBABILISTIC HYBRID UNCERTAINTIES
pp. 387-404
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016979
A PARAMETER SUBSET SELECTION ALGORITHM FOR MIXED-EFFECTS MODELS
pp. 405-416
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016469
MONTE CARLO BASED UNCERTAINTY ANALYSIS FOR VARIABLE PROPERTY MIXED CONVECTION FLOW IN A UNIFORMLY HEATED CIRCULAR TUBE
pp. 417-428
DOI: 10.1615/Int.J.UncertaintyQuantification.2016017195
A MULTIMODES MONTE CARLO FINITE ELEMENT METHOD FOR ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS WITH RANDOM COEFFICIENTS
pp. 429-443
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016805
A NOVEL GLOBAL METHOD FOR RELIABILITY ANALYSIS WITH KRIGING
pp. 445-466
DOI: 10.1615/Int.J.UncertaintyQuantification.2016017441
Dernier numéro
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
Prochains articles
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