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 8, 2018 Выпуск 2
DOI: 10.1615/Int.J.UncertaintyQuantification.v8.i2
INTERVAL-VALUED COMPLEX FUZZY SOFT SET AND ITS APPLICATION
pp. 101-117
DOI: 10.1615/Int.J.UncertaintyQuantification.2018020362
A NOTE ON "NOVEL SINGLE-VALUED NEUTROSOPHIC AGGREGATED OPERATORS UNDER FRANK NORM OPERATION AND ITS APPLICATION TO DECISION-MAKING PROCESS"
pp. 119-121
DOI: 10.1615/Int.J.UncertaintyQuantification.2018024616
A PARTIAL LEAST-SQUARES PATH MODEL FOR MULTIATTRIBUTE DECISION-MAKING UNDER FUZZY ENVIRONMENT
pp. 123-141
DOI: 10.1615/Int.J.UncertaintyQuantification.2018020755
UTILIZING ADJOINT-BASED ERROR ESTIMATES FOR SURROGATE MODELS TO ACCURATELY PREDICT PROBABILITIES OF EVENTS
pp. 143-159
DOI: 10.1615/Int.J.UncertaintyQuantification.2018020911
A NOVEL HYBRID APPROACH FOR SIMPLIFIED NEUTROSOPHIC DECISION-MAKING WITH COMPLETELY UNKNOWN WEIGHT INFORMATION
pp. 161-173
DOI: 10.1615/Int.J.UncertaintyQuantification.2018021164
FAST AND FLEXIBLE UNCERTAINTY QUANTIFICATION THROUGH A DATA-DRIVEN SURROGATE MODEL
pp. 175-192
DOI: 10.1615/Int.J.UncertaintyQuantification.2018021975
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