Selection of the Informative Input Parameters for the Inverse Neural-Network Models of Observed Systems
| Autor: | A. S. Magas, N. А. Guk, N. І. Obodan |
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| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
0209 industrial biotechnology Artificial neural network Applied Mathematics General Mathematics Shell (structure) Inverse 020206 networking & telecommunications 02 engineering and technology Function (mathematics) Inverse problem Grid Stability (probability) 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Algorithm Selection (genetic algorithm) Mathematics |
| Zdroj: | Journal of Mathematical Sciences. 231:678-689 |
| ISSN: | 1573-8795 1072-3374 |
| DOI: | 10.1007/s10958-018-3844-7 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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