scholarly journals Inexact Newton Regularization Using Conjugate Gradients as Inner Iteration

2005 ◽  
Vol 43 (2) ◽  
pp. 604-622 ◽  
Author(s):  
Andreas Rieder
Keyword(s):  
Conjugate Gradients ◽  
Inner Iteration

ACCELERATING TRAINING OF FEEDFORWARD NEURAL NETWORKS

1994 ◽  
Vol 03 (03) ◽  
pp. 339-348
Author(s):  
CARL G. LOONEY
Keyword(s):  
Neural Networks ◽  
Local Minimum ◽  
Random Search ◽  
Feedforward Neural Networks ◽  
Conjugate Gradients ◽  
Activation Functions ◽  
Problematic Behavior ◽  
Methods And Techniques ◽  
Adaptive Step ◽  
Quality Learning

We review methods and techniques for training feedforward neural networks that avoid problematic behavior, accelerate the convergence, and verify the training. Adaptive step gain, bipolar activation functions, and conjugate gradients are powerful stabilizers. Random search techniques circumvent the local minimum trap and avoid specialization due to overtraining. Testing assures quality learning.

scholarly journals A Frame-Based Conjugate Gradients Direct Search Method with Radial Basis Function Interpolation Model

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaowei Fang ◽  
Qin Ni
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Direct Search ◽  
Search Method ◽  
Conjugate Gradients ◽  
Test Problems ◽  
Interpolation Model ◽  
Direct Search Method ◽  
Radial Basis Function Interpolation ◽  
Radial Basis

In this paper, we propose a new hybrid direct search method where a frame-based PRP conjugate gradients direct search algorithm is combined with radial basis function interpolation model. In addition, the rotational minimal positive basis is used to reduce the computation work at each iteration. Numerical results for solving the CUTEr test problems show that the proposed method is promising.

scholarly journals MN-PGSOR Method for Solving Nonlinear Systems with Block Two-by-Two Complex Symmetric Jacobian Matrices

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yu-Ye Feng ◽  
Qing-Biao Wu
Keyword(s):  
Nonlinear Systems ◽  
Iteration Method ◽  
Computing Time ◽  
Coefficient Matrix ◽  
New Method ◽  
Jacobian Matrices ◽  
Modified Newton Method ◽  
Preconditioned Matrix ◽  
Outer Iteration ◽  
Inner Iteration

For solving the large sparse linear systems with 2 × 2 block structure, the generalized successive overrelaxation (GSOR) iteration method is an efficient iteration method. Based on the GSOR method, the PGSOR method introduces a preconditioned matrix with a new parameter for the coefficient matrix which can enhance the efficiency. To solve the nonlinear systems in which the Jacobian matrices are complex and symmetric with the block two-by-two form, we try to use the PGSOR method as an inner iteration, with the help of the modified Newton method as an efficient outer iteration method. This new method is called the modified Newton-PGSOR (MN-PGSOR) method. Local convergence properties of the MN-PGSOR are analyzed under the Hölder condition. Finally, we give the comparison of our new method with some previous methods in the numerical results. The MN-PGSOR method is superior in both iteration steps and computing time.

scholarly journals Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Tinggui Chen ◽  
Renbin Xiao
Keyword(s):  
Product Design ◽  
Iteration Method ◽  
High Performance ◽  
Artificial Bee Colony ◽  
Market Competition ◽  
Processing System ◽  
Design And Development ◽  
Bee Colony ◽  
Design Iteration ◽  
Inner Iteration

Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.

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