Temat: Robust optimization - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Interactive evolutionary multiobjective optimization driven by robust ordinal regression
Autorzy:: Branke, J.
Greco, S.
Słowiński, R.
Zielniewicz, P.
Powiązania:: https://bibliotekanauki.pl/articles/200702.pdf
Data publikacji:: 2010
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: evolutionary multiobjective optimization
interactive procedure
robust ordinal regression
Opis:: This paper presents the Necessary-preference-enhanced Evolutionary Multiobjective Optimizer (NEMO), which combines an evolutionary multiobjective optimization with robust ordinal regression within an interactive procedure. In the course of NEMO, the decision maker is asked to express preferences by simply comparing some pairs of solutions in the current population. The whole set of additive value functions compatible with this preference information is used within a properly modified version of the evolutionary multiobjective optimization technique NSGA-II in order to focus the search towards solutions satisfying the preferences of the decision maker. This allows to speed up convergence to the most preferred region of the Pareto-front.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2010, 58, 3; 347-358
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Generalized ordered linear regression with regularization
Autorzy:: Łęski, J.
Henzel, N.
Powiązania:: https://bibliotekanauki.pl/articles/201591.pdf
Data publikacji:: 2012
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: linear regression
IRLS
OWA
conjugate gradient optimization
robust methods
Opis:: Linear regression analysis has become a fundamental tool in experimental sciences. We propose a new method for parameter estimation in linear models. The 'Generalized Ordered Linear Regression with Regularization' (GOLRR) uses various loss functions (including the o-insensitive ones), ordered weighted averaging of the residuals, and regularization. The algorithm consists in solving a sequence of weighted quadratic minimization problems where the weights used for the next iteration depend not only on the values but also on the order of the model residuals obtained for the current iteration. Such regression problem may be transformed into the iterative reweighted least squares scenario. The conjugate gradient algorithm is used to minimize the proposed criterion function. Finally, numerical examples are given to demonstrate the validity of the method proposed.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 481-489
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Loopshaping of motor torque controller
Autorzy:: Sieklucki, G.
Powiązania:: https://bibliotekanauki.pl/articles/229950.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: electric drive
II2 controller
robust control
stability region
parametric optimization
nonlinear programming
waterbed effect
weighted sensitivity
modulus criterion
Opis:: The controller synthesis problem of the motor torque is presented. The tuning of the II2 controller parameters of the electromagnetic motor torque is introduced. The results are obtained by applying the weighted sensitivity method (nominal performance) which is the optimization in H∞ space. The waterbed effect for some weighting functions is presented. The results, which are obtained by a parametric optimization (nonlinear programming), are analysed by the calculations of the stability margins.
Źródło:: Archives of Control Sciences; 2013, 23, 2; 213-228
1230-2384
Pojawia się w:: Archives of Control Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

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