Name
Abstract | ||
|---|---|---|
A key requirement for using a simulation model to assess a highly complex system is the ability to characterize and quantify the uncertainty in the simulation results with respect to a typically immense set of possible combinations of values of the model's input parameters. Some of these inputs may be sampled from a known or assumed probability distribution, but others are known only possibilistically. A biologically-inspired exploited search model is proposed to assess issues such as hazard, risk, and sensitivity analysis when possibilistic and probabilistic uncertainties interact. Finally, a method for holistic quantification of total uncertainty is presented. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IFSA-NAFIPS.2013.6608595 | PROCEEDINGS OF THE 2013 JOINT IFSA WORLD CONGRESS AND NAFIPS ANNUAL MEETING (IFSA/NAFIPS) |
Keywords | Field | DocType |
Uncertainty, simulation, risk, hazard, sensitivity, biologically inspired computing, exploited search | Data mining,Uncertainty quantification,Computer science,Sensitivity analysis,Uncertainty analysis,Probability distribution,Probabilistic logic,Uncertain systems,Probabilistic simulation | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Whalen | 1 | 115 | 32.39 |
| Brad Morantz | 2 | 0 | 0.34 |
| Murray Cohen | 3 | 0 | 0.34 |