Autor: Fernandez, J. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Numerical Analysis and Simulations of Quasistatic Frictionless Contact Problems
Autorzy:: Fernandez Garcia, J. R.
Han, W.
Shillor, M.
Sofonea, M.
Powiązania:: https://bibliotekanauki.pl/articles/908327.pdf
Data publikacji:: 2001
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: analiza numeryczna
quasistatyka
metoda elementów skończonych
quasistatic contact
Signorini condition
normal compliance
viscoplasticity
variational inequalitie
error estimate
finite element method (FEM)
numerical approximation
Opis:: A summary of recent results concerning the modelling as well as the variational and numerical analysis of frictionless contact problems for viscoplastic materials are presented. The contact is modelled with the Signorini or normal compliance conditions. Error estimates for the fully discrete numerical scheme are described, and numerical simulations based on these schemes are reported.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2001, 11, 1; 205-222
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Minimal Decision Rules Based on the Apriori Algorithm
Autorzy:: Fernandez, M. C.
Menasalvas, E.
Marban, O.
Pena, J. M.
Millan, S.
Powiązania:: https://bibliotekanauki.pl/articles/908364.pdf
Data publikacji:: 2001
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: baza danych
algorytmy
rough sets
rough dependencies
association rules
a priori algorithm
minimal decision rules
Opis:: Based on rough set theory many algorithms for rules extraction from data have been proposed. Decision rules can be obtained directly from a database. Some condition values may be unnecessary in a decision rule produced directly from the database. Such values can then be eliminated to create a more comprehensible (minimal) rule. Most of the algorithms that have been proposed to calculate minimal rules are based on rough set theory or machine learning. In our approach, in a post-processing stage, we apply the Apriori algorithm to reduce the decision rules obtained through rough sets. The set of dependencies thus obtained will help us discover irrelevant attribute values.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2001, 11, 3; 691-704
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Informacja