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1.
Shape optimization of truss-stiffened shell structures with variable thickness
Marko Kegl, Boštjan Brank, 2006, izvirni znanstveni članek

Opis: This paper presents an effective approach to shape optimal design of statically loaded elastic shell-like structures. The shape parametrization is based on a design element technique. The chosen design element is a rational Bézier body, enhanced with a smoothly varying scalar field. A body-like designelement makes possible to unify the shape optimization of both pure shells and truss-stiffened shell structures. The scalar field of the design element is obtained by attaching to each control point a scalar quantity, which is an add-on to the position and weight of the control point. This scalar field is linked to the shell thickness distribution, which can be optimized simultaneously with the shape of the shell. For linear and non-linear analysis of shell structures, a reliable 4-node shell finite element formulation is utilized. The presented optimization approach assumes the employment of a gradient-based optimization algorithm and the use of the discrete method of direct differentiation to perform the sensitivity analysis.Four numerical examples of shell and truss-stiffened shell optimization are presented in detail to illustrate the performance of the proposed approach.
Ključne besede: mechanics of structures, shape optimization, shells, trusses, Bézier body, numerical methods, optimum design
Objavljeno: 30.05.2012; Ogledov: 1107; Prenosov: 67
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2.
Parameter identification of the Jiles-Atherton hysteresis model using differental evolution
Matej Toman, Gorazd Štumberger, Drago Dolinar, 2008, izvirni znanstveni članek

Opis: In this paper, parameters of the Jiles-Atherton (J-A) hysteresis model are identified using a stochastic search algorithm called differential evolution (DE). The J-A hysteresis model's parameters are identified by DE in such a way, that best possible agreement is obtained between the measured and model calculated hysteresis loops. This agreement is furthermore increased by improving the J-A hysteresis model. The improvement is achieved by replacing a constant pinning parameter in the J-A hysteresis model with a variable one. Here, the variable pinning parameter is written as a function of a magnetic field. Bz DE identified parameters are used in the J-A hysteresis model, which is included in the dynamic model of a single-phase transformer. The effectiveness of the improved J-A hysteresis model and parameters identification approach is verified with experiments and simulations.
Ključne besede: Jiles-Atherton model, J-A hysteresis model, magnetic hysteresis, optimization methods, parameters estimation, single-phase transformer
Objavljeno: 31.05.2012; Ogledov: 1265; Prenosov: 32
URL Povezava na celotno besedilo

3.
Organization in finance prepared by stohastic differential equations with additive and nonlinear models and continuous optimization
Pakize Taylan, Gerhard-Wilhelm Weber, 2008, izvirni znanstveni članek

Opis: A central element in organization of financal means by a person, a company or societal group consists in the constitution, analysis and optimization of portfolios. This requests the time-depending modeling of processes. Likewise many processes in nature, technology and economy, financial processes suffer from stochastic fluctuations. Therefore, we consider stochastic differential equations (Kloeden, Platen and Schurz, 1994) since in reality, especially, in the financial sector, many processes are affected with noise. As a drawback, these equations are hard to represent by a computer and hard to resolve. In our paper, we express them in simplified manner of approximation by both a discretization and additive models based on splines. Our parameter estimation refers to the linearly involved spline coefficients as prepared in (Taylan and Weber, 2007) and the partially nonlinearly involved probabilistic parameters. We construct a penalized residual sum of square for this model and face occuring nonlinearities by Gauss-Newton's and Levenberg-Marquardt's method on determining the iteration step. We also investigate when the related minimization program can be written as a Tikhonov regularization problem (sometimes called ridge regression), and we treat it using continuous optimization techniques. In particular, we prepare access to the elegant framework of conic quadratic programming. These convex optimation problems are very well-structured, herewith resembling linear programs and, hence, permitting the use of interior point methods (Nesterov and Nemirovskii, 1993).
Ključne besede: stochastic differential equations, regression, statistical learning, parameter estimation, splines, Gauss-Newton method, Levenberg-Marquardt's method, smoothing, stability, penalty methods, Tikhonov regularization, continuous optimization, conic quadratic programming
Objavljeno: 10.01.2018; Ogledov: 258; Prenosov: 25
.pdf Celotno besedilo (364,34 KB)
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4.
Differential evolution and large-scale optimization applications
Aleš Zamuda, raziskovalni ali dokumentarni film, zvočna ali video publikacija

Opis: Differential Evolution (DE) is one of the most popular, high-performance optimization algorithms with variants that have been outperforming others for years. As a result, DE has grown to accommodate wide usage for a variety of disciplines across scientific fields. Differential Evolution and Large-Scale Optimization Applications presents a research-based overview and cross-disciplinary applications of optimization algorithms. Emphasizing applications of Differential Evolution (DE) across sectors and laying the foundation for further use of DE algorithms in real-world settings, this video is an essential resource for researchers, engineers, and graduate-level students. Topics Covered : Algorithms, Optimization, Parallel Differential Evolution, Performance Improvement, Stochastic Methods, Tree Model Reconstruction.
Ključne besede: differential Evolution, optimization, algorithms, stochastic methods, tree models, tree model reconstruction
Objavljeno: 14.05.2019; Ogledov: 166; Prenosov: 104
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