Results 221 to 230 of about 8,399 (255)

Neural networks as an aid to iterative optimization methods

SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218), 2002
This paper presents an approach of using neural networks to select starting points for iterative methods for optimization problems. Since input/output training data are often available or easily obtained from the problem description, a neural network can be trained to provide a rough model of the optimization problem.
H. J. Li, Andrew H. Sung, William W. Weiss, S. C. Wo   +3 more
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Optimal Multilevel Iterative Methods for Adaptive Grids

SIAM Journal on Scientific and Statistical Computing, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Optimal Parametric Iteration Method

2011
The most common and most widely studied methods for determining analytical approximate solutions of a nonlinear dynamical system are iteration methods.
Vasile Marinca, Nicolae Herisanu
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The Optimal Variational Iteration Method

2011
The variational iteration method was proposed by J. H. He in 1999 [153–155]. The method introduces a reliable and efficient process for a wide variety of scientific and engineering applications, linear and nonlinear, homogeneous or inhomogeneous, equations and systems of equations as well.
Vasile Marinca, Nicolae Herisanu
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Discontinuous solutions of the optimal control problems. Iterative optimization method

Automation and Remote Control, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
V. F. Krotov, Oleg V. Morzhin, Ekaterina A. Trushkova   +2 more
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Iterative Methods in Combinatorial Optimization

2011
With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and ...
Lap Chi Lau, R. Ravi, Mohit Singh
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Optimal disturbances with iterative methods

2009
The flat-plate boundary layer is a classic example of convectively unstable flows; these behave as broadband amplifiers of incoming disturbances. As a consequence, a global stability analysis based on the asymptotic behaviour of single eigenmodes of the system do not capture the relevant dynamics.
Antonios Monokrousos, Espen Åkervik, Luca Brandt, Dan S. Henningson   +3 more
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Constrained optimization of the randomized iterative method

Computational Mathematics and Mathematical Physics, 2009
Summary: Selection of conditionally optimal parameters of the randomized iterative method for solving large scale systems of linear equations is considered. The error of this method is analyzed in analogy to the functional Monte Carlo algorithms. For the simple iteration method, the ``column'' randomization of the matrix is thoroughly analyzed.
Bulgakova, T. E., Vojtishek, A. V.
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An Iterative Method for Inverse Optimal Control

2022 13th Asian Control Conference (ASCC), 2022
Zihao Liang, Wanxin Jin, Shaoshuai Mou
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Optimal Order Iterative Methods

Based on Newton’s method and interpolation method, we establish two iterative methods for solving the nonlinear equations by using n+1 evaluations of the function(or the first derivative) per iteration. Analysis of convergence shows that our methods arrive at the optimal order of convergence 2^n, where the n is any a nature number.
xiang li, xue Wang, jia Wei
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