Results 121 to 130 of about 463,836 (293)
A Quasi-Newton Method with No Derivatives [PDF]
The Davidon formula and others of the “quasi-Newton” class, which are used in the unconstrained minimization of a function f f , provide a (generally) convergent sequence of approximations to the Hessian of f f . These formulas, however, require the independent calculation of the gradient of f f .
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ABSTRACT Geometrically nonlinear static analysis of materially imperfect composite doubly curved shells is investigated via the generalised differential quadrature method. The effects of both shear and thickness deformation are considered through a thickness‐ and shear‐deformable third‐order theory formulated in curvilinear coordinates, while the ...
Behrouz Karami +3 more
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Numerical Modeling of Geological Fault Reactivation Using Sequential Coupling Strategies
ABSTRACT The interaction between fluid flow and mechanical deformation in fault zones can lead to processes of fault reactivation, triggering potential geomechanical problems such as seismicity, well collapse, fluid migration to shallower layers, and aggravated surface subsidence.
Julio Rueda +3 more
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A pilot variational coupled reanalysis based on the CESAM climate model
Variational data assimilation of in‐situ and satellite ocean data and reanalysis atmospheric data into an intermediate complexity Earth system model is possible by adjusting the surface fluxes and internal model parameters. This pilot application requires nearly complete information on the atmospheric state for synchronization.
Armin Köhl +6 more
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Computing the Projection on the Intersection of Linear Equality and Cardinality Constraints
In this paper, we introduce a novel approach to solve the vector projection problem under linear equality and cardinality constraints, termed the Quasi-Newton Lagrangian method. This approach employs a Lagrangian transformation to address linear equality
Xiao-Jing Wang, Zhen-Sheng Yu
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We propose a new method for treating different timescales in coupled variational data assimilation for atmosphere–ocean models. The approach involves a series of short‐window coupled assimilations (red arrows in the schematic) followed by a long‐window correction to the ocean fields (blue arrow).
Amos S. Lawless +3 more
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LEARNING ALGORITHM EFFECT ON MULTILAYER FEED FORWARD ARTIFICIAL NEURAL NETWORK PERFORMANCE IN IMAGE CODING [PDF]
One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is
OMER MAHMOUD +2 more
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ABSTRACT Rationale Ions trapped within a Penning cell (ICR) travel periodic orbits whose frequencies are dependent on their mass‐to‐charge ratio and the value of the magnetic field passing through the trap. Fourier transformation (FT‐ICR) decomposes the signal induced in the detection circuit by the rotation of the ions in the cell after the ...
Patrick Arpino, Michel Heninger
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We delimit the convergence frontier of sparse–matrix quasi-Newton algorithms for rock-blasting simulations. Lip- schitz/Hölder bounds yield Kantorovich radii that mark when the secant matrix preserves contraction.
Fabian León +4 more
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Action constrained quasi-Newton methods
At the heart of Newton based optimization methods is a sequence of symmetric linear systems. Each consecutive system in this sequence is similar to the next, so solving them separately is a waste of computational effort. Here we describe automatic preconditioning techniques for iterative methods for solving such sequences of systems by maintaining an ...
Gower, Robert Mansel, Gondzio, Jacek
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