Name
Abstract | ||
|---|---|---|
Structural modeling is one of the concepts in systems engineering to handle the complexity of technical products. In the process of modeling the choice of the abstraction level and the grade of detail are afflicted with uncertainties. Current methods support in identifying wrong elements or dependencies but support during the verification of the abstraction level is missing. This paper presents an approach to identify errors and not adequately chosen levels of abstraction. Using domain mapping matrices and matrix-multiplication, the approach supports the identification of elements, whose definition should be reconsidered. The approach is applied within an industrial case study. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.procs.2014.03.061 | Procedia Computer Science |
Keywords | Field | DocType |
information acquisition,domain mapping matrix,uncertainty,level of abstraction,complexity management | Data mining,Abstraction,Matrix (mathematics),Computer science,Information acquisition,Abstraction inversion,Abstraction layer,Complexity management | Conference |
Volume | ISSN | Citations |
28 | 1877-0509 | 1 |
PageRank | References | Authors |
0.43 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Roth | 1 | 8 | 3.77 |
| Daniel Kasperek | 2 | 3 | 2.70 |
| Udo Lindemann | 3 | 1 | 0.43 |