International Journal for Uncertainty Quantification
Publicado 6 números por año
ISSN Imprimir: 2152-5080
ISSN En Línea: 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
Volumen 6, 2016 Edición 2
DOI: 10.1615/Int.J.UncertaintyQuantification.v6.i 2
EXPLOSIVE SYNCHRONIZATION OF COMBINATIONAL PHASES ON RANDOM MULTIPLEX NETWORKS
pp. 99-108
DOI: 10.1615/Int.J.UncertaintyQuantification.2016017051
INCORPORATING PRIOR KNOWLEDGE FOR QUANTIFYING AND REDUCING MODEL-FORM UNCERTAINTY IN RANS SIMULATIONS
pp. 109-126
DOI: 10.1615/Int.J.UncertaintyQuantification.2016015984
UNCERTAINTY QUANTIFICATION TOWARDS FILTERING OPTIMIZATION IN SCENE MATCHING AIDED NAVIGATION SYSTEMS
pp. 127-140
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016561
SOFTWARE RELIABILITY GROWTH MODEL WITH TEMPORAL CORRELATION IN A NETWORK ENVIRONMENT
pp. 141-156
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016194
CONSTRUCTION OF EVIDENCE BODIES FROM UNCERTAIN OBSERVATIONS
pp. 157-165
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016572
UNCERTAINTY QUANTIFICATION OF SCIENTIFIC PROPOSAL EVALUATIONS
pp. 167-173
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016198
SEQUENTIAL SPARSITY ITERATIVE OPTIMAL DESIGN MODEL FOR CALIBRATION OF COMPLEX SYSTEMS WITH EPISTEMIC UNCERTAINTY
pp. 175-193
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016845
Último edicion
Próximos Artículos
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