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Parameter identification of the Jiles-Atherton hysteresis model using differental evolution
Matej Toman, Gorazd Štumberger, Drago Dolinar, 2008, original scientific article

Abstract: 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.
Keywords: Jiles-Atherton model, J-A hysteresis model, magnetic hysteresis, optimization methods, parameters estimation, single-phase transformer
Published: 31.05.2012; Views: 1283; Downloads: 32
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Improved frequency characteristics of the randomized PWM boost rectifier
Franc Mihalič, Miro Milanovič, Carlos Cuoto, 2003, original scientific article

Abstract: A randomized pulse width modulation (RPWM) algorithm is applied in the control unit of the boost rectifier to achieve improved frequency characteristics in the wide band. First, the introduction of the RPWM switching is reflected in a smaller increase of the total harmonic distortion (THD) factor in the input current. Nevertheless, decrease of the power factor is negligibly small. Second, the power spectrum density (PSD) of the input current is estimated and measured to evaluate the influence of randomization in the high-frequency range. This approach offers an effective and credible prediction method for reduction of conductive electromagnetic interference (EMI) by using the RPWM switching.
Keywords: rectifiers, boost rectifiers, randomized pulse width modulation, estimation methods, total harmonic distortion, power factor, conductive electromagnetic interference
Published: 01.06.2012; Views: 1033; Downloads: 46
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Tourism sector, travel agencies, and transport suppliers
Nataša Kovačić, Darja Topolšek, Dejan Dragan, 2015, original scientific article

Abstract: The paper addresses the effect of external integration (EI) with transport suppliers on the efficiency of travel agencies in the tourism sector supply chains. The main aim is the comparison of different estimation methods used in the structural equation modeling (SEM), applied to discover possible relationships between EIs and efficiencies. The latter are calculated by the means of data envelopment analysis (DEA). While designing the structural equation model, the exploratory and confirmatory factor analyses are also used as preliminary statistical procedures. For the estimation of parameters of SEM model, three different methods are explained, analyzed and compared: maximum likelihood (ML) method, Bayesian Markov Chain Monte Carlo (BMCMC) method, and unweighted least squares (ULS) method. The study reveals that all estimation methods calculate comparable estimated parameters. The results also give an evidence of good model fit performance. Besides, the research confirms that the amplified external integration with transport providers leads to increased efficiency of travel agencies, which might be a very interesting finding for the operational management.
Keywords: tourism sector, structural equation modeling, estimation methods, external integration, efficiency, travel agencies, logistics
Published: 03.04.2017; Views: 345; Downloads: 90
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Organization in finance prepared by stohastic differential equations with additive and nonlinear models and continuous optimization
Pakize Taylan, Gerhard-Wilhelm Weber, 2008, original scientific article

Abstract: 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).
Keywords: 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
Published: 10.01.2018; Views: 266; Downloads: 25
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