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Wyszukujesz frazę "gradient algorithms" wg kryterium: Temat


Wyświetlanie 1-6 z 6
Tytuł:
Optimization of material distribution for forged automotive components using hybrid optimization techniques
Autorzy:
Sebastjan, Przemysław
Kuś, Wacław
Powiązania:
https://bibliotekanauki.pl/articles/29520109.pdf
Data publikacji:
2021
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
shape optimization
hybrid optimization
genetic algorithms
evolutionary algorithms
gradient algorithms
auto-motive part optimization
Opis:
The paper deals with the problem of optimal material distribution inside the provided design area. Optimization based on deterministic and stochastic algorithms is used to obtain the best result on the basis of the proposed objective function and constraints. The optimization of the shock absorber is used as an example of the described methods. One of the main difficulties addressed is the manufacturability of the optimized part intended for the forging process. Additionally, nonlinear buckling simulation with the use of the finite element method is used to solve the misuse case of shock absorber compression, where the shape of the optimized part has a key role in the total strength of the automotive damper. All of that, together with the required design precision, creates the nontrivial constrained optimization problem solved using the parametric, implicit geometry representation and a combination of stochastic and deterministic algorithms used with parallel design processing. Two methods of optimization are examined and compared in terms of the total amount of function calls, final design mass, and feasibility of the resultant design. Also, the amount of parameters used for the implicit geometry representation is greatly reduced compared to existing schemes presented in the literature. The problem addressed in this article is strongly inspired by the actual industrial example of the mass minimization process, but it is more focused on the actual manufacturability of the resultant component and admissible solving time. Commercially accessible software combined with authors’ procedures is used to resolve the material distribution task, which makes the proposed method universal and easily adapted to other fields of the optimization of mechanical elements.
Źródło:
Computer Methods in Materials Science; 2021, 21, 2; 63-74
2720-4081
2720-3948
Pojawia się w:
Computer Methods in Materials Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The analysis of gradient algorithm effectiveness - two dimensional heat transfer problem
Autorzy:
Łopata, S.
Ocłoń, P.
Powiązania:
https://bibliotekanauki.pl/articles/240515.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
algorytm gradientów
metoda regulacji głośności
wymiana ciepła
control volume method
gradient algorithms
heat transfer
Opis:
The analysis of effectiveness of the gradient algorithm for the two-dimension steady state heat transfer problems is being performed. The three gradient algorithms - the BCG (biconjugate gradient algorithm), the BICGSTAB (biconjugate gradient stabilized algorithm), and the CGS (conjugate gradient squared algorithm) are implemented in a computer code. Because the first type boundary conditions are imposed, it is possible to compare the results with the analytical solution. Computations are carried out for different numerical grid densities. Therefore it is possible to investigate how the grid density influences the efficiency of the gradient algorithms. The total computational time, residual drop and the iteration time for the gradient algorithms are additionally compared with the performance of the SOR (successive over-relaxation) method.
Źródło:
Archives of Thermodynamics; 2010, 31, 4; 37-50
1231-0956
2083-6023
Pojawia się w:
Archives of Thermodynamics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sub-gradient algorithms for computation of extreme eigenvalues of a real symmetric matrix
Autorzy:
Yassine, A.
Powiązania:
https://bibliotekanauki.pl/articles/205834.pdf
Data publikacji:
1998
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
problem wartości własnej
difference of convex functions
eigenvalue problems
Lagrangian duality
non-convex optimization
sub-gradient algorithms
Opis:
The computation of eigenvalues of a matrix is still of importance from both theoretical and practical points of view. This is a significant problem for numerous industrial and scientific situations, notably in dynamics of structures (e.g. Gerardin, 1984), physics (e.g. Rappaz, 1979), chemistry (e.g. Davidson, 1983), economy (e.g. Morishima, 1971; Neumann, 1946), mathematics (e.g. Golub, 1989; Chatelin, 1983, 1984, 1988). The study of eigenvalue problems remains a delicate task, which generally presents numerical difficulties in relation to its sensivity to roundoff errors that may lead to numerical unstabilities, particularly if the eigenvalues are not well separated. In this paper, new subgradient-algorithms for computation of extreme eigenvalues of a symmetric real matrix are presented. Those algorithms are based on stability of Lagrangian duality for non-convex optimization and on duality in the difference of convex functions. Some experimental results which prove the robustness and efficiency of our algorithms are provided.
Źródło:
Control and Cybernetics; 1998, 27, 3; 387-415
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm
Autorzy:
Boboń, A.
Nocoń, A.
Paszek, S.
Pruski, P.
Powiązania:
https://bibliotekanauki.pl/articles/200774.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
gradient optimization algorithms
synchronous generator model
parameter estimation
load rejection test
algorytm optymalizacji gradientu
modele generatorów synchronicznych
estymacja parametrów
test odrzucenia ładunku
Opis:
The paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2017, 65, 4; 479-488
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Convergence Analysis of Multilayer Feedforward Networks Trained with Penalty Terms: A review
Autorzy:
Wang, J.
Yang, G.
Liu, S.
Zurada, J. M.
Powiązania:
https://bibliotekanauki.pl/articles/108639.pdf
Data publikacji:
2015
Wydawca:
Społeczna Akademia Nauk w Łodzi
Tematy:
Gradient
feedforward neural networks
generalization
penalty
convergence
pruning algorithms
Opis:
Gradient descent method is one of the popular methods to train feedforward neural networks. Batch and incremental modes are the two most common methods to practically implement the gradient-based training for such networks. Furthermore, since generalization is an important property and quality criterion of a trained network, pruning algorithms with the addition of regularization terms have been widely used as an efficient way to achieve good generalization. In this paper, we review the convergence property and other performance aspects of recently researched training approaches based on different penalization terms. In addition, we show the smoothing approximation tricks when the penalty term is non-differentiable at origin.
Źródło:
Journal of Applied Computer Science Methods; 2015, 7 No. 2; 89-103
1689-9636
Pojawia się w:
Journal of Applied Computer Science Methods
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The use of mathematical and computer modelling in solving the problems or rail transport expert examination
Autorzy:
Kuzin, N.
Meshcheryakova, T.
Kuzin, O.
Kurileva, E.
Gordinskaya, N.
Powiązania:
https://bibliotekanauki.pl/articles/122500.pdf
Data publikacji:
2016
Wydawca:
Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:
forensic examination
inverse problems of fracture mechanics
functionally gradient materials
numerical algorithms
materiały gradientowe
algorytmy numeryczne
mechanika pękania
Opis:
The analysis of the current state of expert research of the failure of structural elements of railway rolling stock is presented. On the basis of the approaches of mechanics, mathematical and computer modeling the technique of establishing a mechanism for softening of parts and units of friction in the operation of rail transport is suggested.
Źródło:
Journal of Applied Mathematics and Computational Mechanics; 2016, 15, 4; 93-98
2299-9965
Pojawia się w:
Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-6 z 6

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