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IPSAL: Implementation of the module to generate the Sobol sequence and indices

Authors :
Luiz Felipe Alves Borges
Fabio Freitas Ferreira
Fábio Gonçalves
Antônio Espósito Junior
Aline Fernanda da Silva Oliveira
Wagner Rambaldi Telles
Source :
Vetor, Vol 33, Iss 2 (2023)
Publication Year :
2023
Publisher :
Universidade Federal do Rio Grande, 2023.

Abstract

Sensitivity and uncertainty analysis hold significant importance across a range of applications, spanning from industrial problems to climate change, financial risk assessment, as well as mathematical and computational models. These analyses involve identifying influential input parameters in models to comprehend their impact on the output. Sensitivity analysis can be performed locally, examining parameter effects at a fixed value, or globally, evaluating the model across a range of parameter values. The Sobol method stands as a robust approach for global sensitivity analysis, employing a Sobol sequence to create samples more uniformly within the input parameter space, thus enabling efficient exploration of model inputs. This paper aims to introduce a computational implementation in Scilab to generate the Sobol sequence for utilization in sensitivity analysis through the Sobol method. A test case was applied to generate Sobol sequences and discuss the obtained results.

Details

Language :
English, Portuguese
ISSN :
01027352 and 23583452
Volume :
33
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Vetor
Publication Type :
Academic Journal
Accession number :
edsdoj.9d46d942b3b74444bd2441c0e77451ee
Document Type :
article
Full Text :
https://doi.org/10.14295/vetor.v33i2.16439