Conjugate gradient
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
... [50] proposed a three-term PRP conjugate gradient algorithm by using the projection-based technique, which was introduced by Solodov et al.[51] for optimization problems. The projec- tion-based technique is ...
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Using Conjugate Gradient Network to Classify Stress Level of Patients.
... 88%. Much of our classifiers’ confusion seen in the results can be explained with transitions from one activity to another. The annotator was not given the choice to annotate “transition,” but he had to switch from one ...
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A cooperative conjugate gradient method for linear systems permitting efficient multi-thread implementation
... In Gu et al. (2004a, b), the authors present a multi-thread CG method named “multi- ple search direction conjugate gradient method” (MSD-CG), and its preconditioned version (PMSD-CG). The method is midway ...
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TEMA (São Carlos) vol.16 número3
... We considered the solution of an ill-conditioned least-squares problem arising from the dis- cretization of a model for linear seismic tomography, which is a tool with wide application in reservoir geophysics. The ...
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J. Braz. Soc. Mech. Sci. & Eng. vol.28 número1
... the conjugate gradient method and with the hybrid optimization approach by using only two sensors (see ...the conjugate gradient method is not as sensitive to the fact that the problem is ...
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Comput. Appl. Math. vol.31 número1
... conjugate gradient methods in practical computation and studied extensively. Now let us simply introduce some results on the PRP method. The global con- vergence of the PRP method with exact line search has ...
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Application of Artificial Neural Network For Path Loss Prediction In Urban Macrocellular Environment
... MLP network of different sizes were analyzed to determine the network complexity required to obtain accurate path loss predictions. To reduce the training time and still maintain the prediction accuracy and ...
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A STUDY ON CERTAIN NEW NUMERICAL ALGORITHMS FOR MINIMIZATION OF NON LINEAR FUNCTIONS
... nonlinear conjugate gradient methods [8], a scaled nonlinear conjugate gradient algorithm[2], a method called, ABS-MPVT algorithm [10] are used for solving unconstrained optimization ...
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Comput. Appl. Math. vol.28 número1
... By the same argument as Algorithm 2.1, we can get the following three-term HS method. In the rest of this paper, we only give the direction in the algorithm where the other steps are as same as Algorithm 2.1 since ...
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Comput. Appl. Math. vol.22 número1
... The fluid velocity on the drop interfaces are obtained by an iterative solution of (36) using the GMRES algorithm (a generalization of the conjugate gradient method to non-symmetric matr[r] ...
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Numerical Mathematics Livros e Materiais Online Evandro Marquesone
... the gradient method, while the solid and circled lines refer respectively to the conjugate gradient (CG) and SOR method (with an optimal value of the relaxation parameter ω ≃ ...
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SEISMIC TRAVELTIME TOMOGRAPHY IN THE DOM JOÃO FIELD, RECÔNCAVO BASIN, BRAZIL
... ABSTRACT. Tomography was incorporated in Exploration Geophysics with the intention of providing high-resolution images of regions in Earth’s subsurface that are characterized as potential reservoirs. In this work, ...
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Real-time 3D rendering of water using CUDA
... The Conjugate Gradient method, in both versions, gives slightly better water shaped effects than in the other two ...of Conjugate Gradient is only used on the diffusion of velocities and ...
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Predicting for Sustainable Insurance with Adaptive Gradient Methods
... (simple gradient descent) uses first order information to descend toward the point of local ...like conjugate gradient, scaled conjugate gradient, which have their own positives and ...
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Comput. Appl. Math. vol.27 número1
... some conjugate gradient methods have good numerical performance in solving large scale minimization problems, they have no global convergence in some situations ...a conjugate gradient method ...
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A regularized GMRES method for inverse blackbody radiation problem
... scholars' attention. The first formulation for this problem was proposed by Bojarski [2] in 1982. The Laplace transform together with an iterative process was presented. Chen and Li [3], Dai and Dai [4] proved the ...
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First and second order training algorithms for artificial neural networks to detect the cardiac state
... as conjugate gradient, scaled conjugate gradients, Newton’s method, Quasi-Newton methods, Limited memory quasi-Newton methods and Levenberg-Marquardt ...
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Comput. Appl. Math. vol.25 número1
... compare Conjugate Gradient with those methods, but to show that our approximation of GCV is applicable as a stopping rule to the Conjugate Gradient method for large scale ill-posed problems, ...
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AN ECOSYSTEMIC VIEW FOR DEVELOPING BIOLOGICALLY PLAUSIBLE OPTIMIZATION SYSTEMS THESIS
... using a Monte Carlo method hybridised with Newtonian conjugate gradient minimisation (STILLINGER; HEAD-GORDON, 1995); PBHS is the best result obtained by a population- based Harmony Sear[r] ...
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Some Research Methodologies in Applied and Computational Mathematics
... Also make comparison between the block SOR methods and the preconditioned conjugate gradient method (A.N. Iusem and J.Y. Yuan, Preconditioned SOR Methods for Generalized Least Squares Pr[r] ...
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