Selection of the Informative Input Parameters for the Inverse Neural-Network Models of Observed Systems
- Authors: Obodan N.І.1, Guk N.А.1, Magas A.S.1
-
Affiliations:
- Honchar Dnipropetrovs’k National University
- Issue: Vol 231, No 5 (2018)
- Pages: 678-689
- Section: Article
- URL: https://journals.rcsi.science/1072-3374/article/view/241215
- DOI: https://doi.org/10.1007/s10958-018-3844-7
- ID: 241215
Cite item
Abstract
We consider the problem of determination of the parameters of a measurement grid, which guarantees the exactness and stability of the solution of the inverse problem. The choice of the points of measurements is performed under the assumption of existence of the most informative data. We present the results illustrating the influence of the number of measurement points on the data of reconstruction of the parameters of the load function acting upon the cylindrical shell in a strip located along the length of the shell.
About the authors
N. І. Obodan
Honchar Dnipropetrovs’k National University
Email: Jade.Santos@springer.com
Ukraine, Dnipropetrovs’k
N. А. Guk
Honchar Dnipropetrovs’k National University
Email: Jade.Santos@springer.com
Ukraine, Dnipropetrovs’k
A. S. Magas
Honchar Dnipropetrovs’k National University
Email: Jade.Santos@springer.com
Ukraine, Dnipropetrovs’k