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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 29 for “"BFGS"”.
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Data Reduction Procedure for an Experimental Method of Measuring the Velocity-Coupled Response Function of Solid Propellants
… consists of a Runge-Kutta routine driven by a BFGS multivariable search routine. The Runge-Kutta routine determines the pressure distribution within the chamber of the proposed apparatus for a specific velocity-coupled response function (Rv). The BFGS optimization routine searches for the Rv …
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Tracking on manifolds : quasi-Newton optimisation algorithms on manifolds
… on manifolds. In 1982, Gabay proposed a BFGS algorithm (which is a popular quasi-Newton algorithm) to Riemannian manifolds. The convergence proof was not completed. This thesis will continue his attempts on the proof of convergence results. A more challenging task will be brought to …
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Estratégias de inversão de multiparâmetros utilizando a equação completa da elastodinâmica
… (PolakRibi`ere and Fletcher-Reeves) and the l-BFGS (Quasi-Newton). This analysis reinforces that the l-BFGS method, which makes Hessian approximations iteratively, is the one that better estimates the resulting model, besides converges faster to a satisfactory model. Also, it is evaluated the …
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On the Use of Quasi-Newton Methods for the Minimization of Convex Quadratic Splines
… of Broyden, Fletcher, Goldfarb, and Shanno (BFGS) is investigated as a tool to solve the unconstrained minimization problem. It is shown that there is a linear convergence rate and, for nondegenerate problems, the process terminates in a finite number of iterations. Numerical examples are …
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
… Halley with Broyden-Fletcher-Goldfarb�Shanno (H-BFGS) and Halley with Davidon-Fletcher-Powell (H-DFP). The efficiency of the proposed methods is compared with the first and second order optimisation method by means of simulation on UCI Machine Learning Repository, Knowledge Extraction …
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Solving The Prandtl Boundary Layer Equation in Fluid Dynamics Via Non-Linear Numerical Optimization
… of the Quasi-Newton methods known as the BFGS Quasi-Newton iteration is applied with a quadratic convergence rate [41][43] while the conventional FVM converges linearly using the SIMPLE iteration approach. In this work, an Objective Function (or Penalty Function) and a gradient vector, as …
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Estimação clássica e Bayesiana em modelos de sobrevida com fração de cura
… used were numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation (own implementation) and Gibbs sampling as implemented in Winbugs. We describe the main features of the models used, the estimation methods and the computational aspects. We also discuss …
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Multiclass Origin-Destination Estimation Using Multiple Data Types
… using various types of data. Limited memory BFGS method with bounded constraints is used for solving the upper level optimization, which is used to derive O-D table entries by minimizing the sum of squared differences between observations from different data sources and the predictions of …
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Traversing Rugged Domains: Explorations in Non-convex Optimization Theory and Software
… combining Particle Swarm Optimization with L-BFGS, and an augmented Lagrangian approach with stochastic inner optimizers that connects constrained optimization with machine learning techniques. Our work combines theoretical foundations with practical implementation, providing researchers tools …
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In Pursuit of Local Correlation for Reduced-Scaling Electronic Structure Methods in Molecules and Periodic Solids
… limited-memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) based Pipek-Mezey Wannier function (PMWF) solver [Clement, et al. 2021 }, Submitted to J. Chem. Theory Comput.]. Although orbital localization in the context of the linear combination of atomic orbitals (LCAO) representation of periodic …
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Design Optimization Of Solid Rocket Motor Grains For Internal Ballistic Performance
… include DOE, genetic algorithms, and the BFGS first-order gradient-based algorithm. This strategy was successfully applied to the design of three solid rocket motor grains of varying complexity. The contributions of this work was the development and application of an optimization strategy …
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A structured reduced sequential quadratic programming and its application to a shape design problem
… this, Sequential quadratic programming with BFGS update for the reduced Hessian of the Lagrangian function is used with Variable reduction method which preserves the structure of the Jacobian in representing the null space basis matrix. By updating the reduced Hessians only of which the …
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Techniques for Reliability and Robustness in Integrated Electronic and Photonic Systems
… significantly outperform the gradient-based L-BFGS-B algorithm. New schemes for strategic failure analysis on a subset of the failed units are presented, both for detecting the presence of a second failure mechanism and for improving two-mechanism reliability models. A regression-based protocol …
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Computational optimization of phase change materials on adsorbed carbon dioxide capture systems
… domain isotherms and kinetics. Utilizing the L-BFGS optimization method, a distribution of phase change material within an activated carbon adsorbent bed was determined to improve (CO2) uptake across device designs indicating feasibility for next generation designs.
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Placing limits on the Higgs production cross section at the tevatron using the H to W+W- to l+l- decay channel
… the sensitivity of the measurement. The BFGS neuralnet training technique was selected as the most efficient method. A Bayesian Likelihood technique was used to place limits on the observed Higgs production cross section, and an expected limit was calculated by running 10,000 pseudo …
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Large-Scale Simulations Using First and Second Order Adjoints with Applications in Data Assimilation
… scenarios. The results indicate that the L-BFGS method is the most efficient. Compared with first order adjoints, second order adjoints have not been used to date in air quality simulation. To explore their utility, we show the construction of second order adjoints for chemical transport …
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From Hartree Product to Kohn-Sham and Beyond: Exploring Self-Interaction in Self-Consistent Field Methods
… (TR); to be economical, the solver uses an L-BFGS approximate Hessian and a physically-relevant preconditioner. Coupling these two aspects together is a solver for the TR subproblem that exploits the low-rank structure of the L-BFGS Hessian. We demonstrate that QUOTR is useful, not only for …
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Towards Real-Time Simulation Of Hyperelastic Materials
… our solver can be further accelerated using L-BFGS updates (Limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm). Our final method is typically more than ten times faster than one iteration of Newton's method without compromising quality. In fact, our result is often more accurate than …
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Scaling rank-one updating formula and its application in unconstrained optimization
… that the new method compares favourably with BFGS. Using the OCSSRl update, we propose a hybrid QN algorithm which does not need to store any matrix. Numerical results show that it is a very promising method for solving large scale optimization problems. In addition, some popular technologies …
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Scaling rank-one updating formula and its application in unconstrained optimization
… that the new method compares favourably with BFGS. Using the OCSSRl update, we propose a hybrid QN algorithm which does not need to store any matrix. Numerical results show that it is a very promising method for solving large scale optimization problems. In addition, some popular technologies …
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