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
Prochains articles
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